Accessibility navigation


Items where Author is "Hong, Professor Xia"

Up a level
Export as [feed] Atom [feed] RSS 1.0 [feed] RSS 2.0
[tool] Batch List
Group by: Item Type | No Grouping
Number of items: 190.

Article

Zhang, J., Xiao, J., Chen, M. and Hong, X. (2023) Multimodal continual learning for process monitoring: a novel weighted canonical correlation analysis with attention mechanism. IEEE Transactions on Neural Networks and Learning Systems. ISSN 2162-237X doi: https://doi.org/10.1109/TNNLS.2023.3331732

Zhang, J., Chen, M. and Hong, X. (2023) Monitoring multimode nonlinear dynamic processes: an efficient sparse dynamic approach with continual learning ability. IEEE Transactions on Industrial Informatics, 19 (7). pp. 8029-8038. ISSN 1941-0050 doi: https://doi.org/10.1109/TII.2022.3215971

Zhang, J., Zhou, D., Chen, M. and Hong, X. (2023) Continual learning-based probabilistic slow feature analysis for monitoring multimode nonstationary processes. IEEE Transactions on Automation Science and Engineering. ISSN 1558-3783 doi: https://doi.org/10.1109/TASE.2022.3219125

Hong, X., Gao, J., Wei, H., Xiao, J. and Mitchell, R. (2023) Two-step scalable spectral clustering algorithm using landmarks and probability density estimation. Neurocomputing, 519. pp. 173-186. ISSN 0925-2312 doi: https://doi.org/10.1016/j.neucom.2022.11.063

Zhang, J., Zhou, D., Chen, M. and Hong, X. (2023) Continual learning for multimode dynamic process monitoring with applications to an ultra–supercritical thermal power plant. IEEE transactions on Automation Science and Engineering, 20 (1). pp. 137-150. ISSN 1558-3783 doi: https://doi.org/10.1109/TASE.2022.3144288

Zhang, J., Chen, M. and Hong, X. (2021) Nonlinear process monitoring using a mixture of probabilistic PCA with clusterings. Neurocomputing, 458. pp. 319-326. ISSN 0925-2312 doi: https://doi.org/10.1016/j.neucom.2021.06.039

Hong, X. and Gao, J. (2021) Estimating the square root of probability density function on Riemannian manifold. Expert Systems: International Journal of Knowledge Engineering, 38 (7). e12266. ISSN 1468-0394 doi: https://doi.org/10.1111/exsy.12266

Shi, D., Gao, J., Hong, X., Choy, S. T. B. and Wang, Z. (2021) Coupling matrix manifolds assisted optimization for optimal transport problems. Machine Learning, 110. pp. 533-558. ISSN 1573-0565 doi: https://doi.org/10.1007/s10994-020-05931-2

Feng, Y. and Hong, X. (2021) Parameter tracking of time-varying Hammerstein-Wiener Systems. International Journal of Systems Science, 52 (16). pp. 3478-3492. ISSN 0020-7721 doi: https://doi.org/10.1080/00207721.2021.1931546

Hong, X., Gao, J. and Chen, S. (2020) Semi-blind joint channel estimation and data detection on sphere manifold for MIMO with high-order QAM signaling. Journal of the Franklin Institute, 357 (9). pp. 5680-5690. ISSN 0016-0032 doi: https://doi.org/10.1016/j.jfranklin.2020.04.009

Hong, X., Mitchell, R. and Di Fatta, G. (2019) Simplex basis function based sparse least squares support vector regression. Neurocomputing, 330. pp. 394-402. ISSN 0925-2312 doi: https://doi.org/10.1016/j.neucom.2018.11.025

Zhang, J., Chen, H., Chen, S. and Hong, X. (2019) An improved mixture of probabilistic PCA for nonlinear data-driven process monitoring. IEEE Transactions on Cybernetics, 49 (1). pp. 198-210. ISSN 2168-2267 doi: https://doi.org/10.1109/TCYB.2017.2771229

Zhang, J., Chen, M., Chen, H., Hong, X. and Zhou, D. (2019) Process monitoring based on orthogonal locality preserving projection with maximum likelihood estimation. Industrial & Engineering Chemistry Research, 58 (14). pp. 5579-5587. ISSN 1520-5045 doi: https://doi.org/10.1021/acs.iecr.8b05875

Hong, X. and Chen, S. (2017) Recursive least squares semi-blind beamforming for MIMO using decision directed adaptation and constant modulus criterion. International Journal of Automation and Computing, 14 (4). pp. 442-449. ISSN 1476-8186 doi: https://doi.org/10.1007/s11633-017-1087-6

Chen, S., Hong, X., Khalaf, E. F., Morfeq, A., Alotaibi, N. D. and Harris, C. J. (2017) Single-carrier frequency-domain equalization with hybrid decision feedback equalizer for Hammerstein channels containing nonlinear transmit amplifier. IEEE Transactions on Wireless Communications, 16 (5). pp. 3341-3354. ISSN 1536-1276 doi: https://doi.org/10.1109/TWC.2017.2681083

Hong, X., Gao, J. and Chen, S. (2017) Zero attracting recursive least squares algorithms. IEEE Transactions on Vehicular Technology, 66 (1). 213 -221. ISSN 0018-9545 doi: https://doi.org/10.1109/TVT.2016.2533664

Chen, S., Hong, X., Khalaf, E. F., Alsaadi, F. E. and Harris, C. J. (2017) Comparative performance of complex-valued B-spline and polynomial models applied to iterative frequency-domain decision feedback equalization of Hammerstein channels. IEEE Transactions on Neural Networks and Learning Systems, 28 (12). pp. 2872-2884. ISSN 2162-237X doi: https://doi.org/10.1109/TNNLS.2016.2609001

Hong, X., Chen, S., Guo, Y. and Gao, J. (2017) l1-norm penalized orthogonal forward regression. International Journal of Systems Science, 48 (10). pp. 2195-2201. ISSN 0020-7721 doi: https://doi.org/10.1080/00207721.2017.1311383

Chen, H., Gong, Y., Hong, X. and Chen, S. (2016) A fast adaptive tunable RBF network for nonstationary systems. IEEE Transactions on Cybernetics, 46 (12). pp. 2683-2692. ISSN 2168-2267 doi: https://doi.org/10.1109/TCYB.2015.2484378

Fu, Y., Gao, J., Tien, D., Lin, Z. and Hong, X. (2016) Tensor LRR and sparse coding-based subspace clustering. IEEE Transactions on Neural Networks and Learning Systems, 27 (10). pp. 2120-2133. ISSN 2162-237X doi: https://doi.org/10.1109/TNNLS.2016.2553155

Sun, Y., Gao, J., Hong, X., Mishra, B. and Yin, B. (2016) Heterogeneous tensor decomposition for clustering via manifold optimization. IEEE Transactions on Pattern Analysis and Machine Intelligence, 38 (3). pp. 476-489. ISSN 0162-8828 doi: https://doi.org/10.1109/TPAMI.2015.2465901

Hong, X., Chen, S. and Becerra, V. (2016) Sparse density estimator with tunable kernels. Neurocomputing, 173 (3). pp. 1976-1982. ISSN 0925-2312 doi: https://doi.org/10.1016/j.neucom.2015.08.021

Chen, H., Gong, Y. and Hong, X. (2016) A new adaptive multiple modelling approach for non-linear and non-stationary systems. International Journal of Systems Science, 47 (9). pp. 2100-2110. ISSN 0020-7721 doi: https://doi.org/10.1080/00207721.2014.973926

Hong, X., Gao, J., Chen, S. and Zia, T. (2015) Sparse density estimation on the multinomial manifold. IEEE Transactions on Neural Networks and Learning Systems, 26 (11). pp. 2972-2977. ISSN 2162-237X doi: https://doi.org/10.1109/TNNLS.2015.2389273

Chen, S., Hong, X., Khalaf, E., Morfeq, A. and Alotaibi, N. D. (2015) Adaptive B-spline neural network based nonlinear equalization for high-order QAM systems with nonlinear transmit high power amplifier. Digital Signal Processing, 40. pp. 238-249. ISSN 1051-2004 doi: https://doi.org/10.1016/j.dsp.2015.02.006

Hong, X. and Chen, S. (2015) Elastic net orthogonal forward regression. Neurocomputing, 148. pp. 551-560. ISSN 0925-2312 doi: https://doi.org/10.1016/j.neucom.2014.07.008

Hong, X., Chen, S., Gao, J. and Harris, C. J. (2015) Nonlinear identification using orthogonal forward regression with nested optimal regularization. IEEE Transactions on Cybernetics, 45 (12). pp. 2925-2936. ISSN 2168-2267 doi: https://doi.org/10.1109/TCYB.2015.2389524

Hong, X., Chen, S., Gong, Y. and Harris, C. J. (2014) Nonlinear equalization of Hammerstein OFDM systems. IEEE Transactions on Signal Processing, 62 (21). pp. 5629-5639. ISSN 1053-587X doi: https://doi.org/10.1109/TSP.2014.2355773

Chen, H., Gong, Y., Hong, X. and Chen, S. (2014) Adaptive nonlinear equalizer using a mixture of gaussians based on-line density estimator. IEEE Transactions on Vehicular Technology, 63 (9). pp. 4265-4276. ISSN 0018-9545 doi: https://doi.org/10.1109/TVT.2014.2313458

Hong, X., Gao, J., Jiang, X. and Harris, C. J. (2014) Estimation of Gaussian process regression model using probability distance measures. Systems Science & Control Engineering, 2. pp. 655-663. ISSN 2164-2583 doi: https://doi.org/10.1080/21642583.2014.970731

Hong, X., Chen, S., Harris, C. J. and Khalaf, E. F. (2014) Single-carrier frequency domain equalisation for hammerstein communication systems using complex-valued neural networks. IEEE Transactions on Signal Processing, 62 (17). pp. 4467-4478. ISSN 1053-587X doi: https://doi.org/10.1109/TSP.2014.2333555

Chen, S., Hong, X., Gao, J. and Harris, C.J. (2014) Complex-valued B-spline neural networks for modeling and inverting Hammerstein systems. IEEE Transactions on Neural Networks and Learning Systems, 25 (9). pp. 1673-1685. ISSN 2162-237X doi: https://doi.org/10.1109/TNNLS.2014.2298535

Gao, M., Hong, X., Chen, S., Harris, C. J. and Khalaf, E. (2014) PDFOS: PDF estimation based over-sampling for imbalanced two-class problems. Neurocomputing, 138. pp. 248-259. ISSN 0925-2312 doi: https://doi.org/10.1016/j.neucom.2014.02.006

Hong, X., Chen, S., Qatawneh, A., Daqrouq, K., Sheikh, M. and Morfeq, A. (2014) A radial basis function network classifier to maximise leave-one-out mutual information. Applied Soft Computing, 23. pp. 9-18. ISSN 1568-4946 doi: https://doi.org/10.1016/j.asoc.2014.06.003

Hong, X., Gao, J., Jiang, X. and Harris, C. J. (2014) Fast identification algorithms for Gaussian process model. Neurocomputing, 133. pp. 25-31. ISSN 0925-2312 doi: https://doi.org/10.1016/j.neucom.2013.11.035

Hong, X., Iplikci, S., Chen, S. and Warwick, K. (2014) A model-based PID controller for Hammerstein systems using B-spline neural networks. International Journal of Adaptive Control and Signal Processing, 28 (3-5). pp. 412-428. ISSN 0890-6327 doi: https://doi.org/10.1002/acs.2293

Gao, M., Hong, X. and Harris, C. J. (2014) Construction of neurofuzzy models for imbalanced data classification. IEEE Transactions on Fuzzy Systems, 22 (6). pp. 1472-1488. ISSN 1063-6706 doi: https://doi.org/10.1109/TFUZZ.2013.2296091

Gao, M., Hong, X. and Harris, C. J. (2014) A unified neurofuzzy model for classification. International Journal of Systems Science, 45 (10). pp. 2158-2171. ISSN 0020-7721 doi: https://doi.org/10.1080/00207721.2013.763301

Hong, X., Chen, S., Qatawneh, A., Daqrouq, K., Sheikh, M. and Morfeq, A. (2013) Sparse probability density function estimation using the minimum integrated square error. Neurocomputing, 114. pp. 122-129. ISSN 0925-2312 doi: https://doi.org/10.1016/j.neucom.2013.02.003

Hong, X., Gao, J., Chen, S. and Harris, C. J. (2013) Particle swarm optimisation assisted classification using elastic net prefiltering. Neurocomputing, 122. pp. 210-220. ISSN 0925-2312 doi: https://doi.org/10.1016/j.neucom.2013.06.030

Chen, S., Hong, X., Gong, Y. and Harris, C. J. (2013) Digital predistorter design using B-Spline neural network and inverse of De Boor algorithm. IEEE Transactions on Circuits and Systems Part I: fundamental theory and applications, 60 (6). pp. 1584-1594. ISSN 1057-7122 doi: https://doi.org/10.1109/TCSI.2012.2226514

Chen, H., Gong, Y. and Hong, X. (2013) Online modeling with tunable RBF network. IEEE Transactions on Cybernetics, 43 (3). pp. 935-947. ISSN 2168-2267 doi: https://doi.org/10.1109/TSMCB.2012.2218804

Hong, X., Chen, S. and Harris, C. J. (2013) Elastic-net prefiltering for two-class classification. IEEE Transactions on Cybernetics, 43 (1). pp. 286-295. ISSN 2168-2267 doi: https://doi.org/10.1109/TSMCB.2012.2205677

Hong, X., Mitchell, R. J. and Chen, S. (2013) System identification of Wiener systems with B-spline functions using De Boor recursion. International Journal of Systems Science, 44 (9). pp. 1666-1674. ISSN 0020-7721 doi: https://doi.org/10.1080/00207721.2012.669863

Hong, X., Chen, S. and Harris, C. (2012) Using zero-norm constraint for sparse probability density function estimation. International Journal of Systems Science, 43 (11). pp. 2107-2113. ISSN 0020-7721 doi: https://doi.org/10.1080/00207721.2011.564673

Hong, X., Mitchell, R. and Chen, S. (2012) Modelling and control of Hammerstein system using B-spline approximation and the inverse of De Boor algorithm. International Journal of Systems Science, 43 (10). pp. 1976-1984. ISSN 0020-7721 doi: https://doi.org/10.1080/00207721.2011.564320

Hong, X. and Chen, S. (2012) The system identification and control of Hammerstein system using non-uniform rational B-spline neural network and particle swarm optimization. Neurocomputing, 82. pp. 216-223. ISSN 0925-2312 doi: https://doi.org/10.1016/j.neucom.2011.11.016

Li, K., Hong, X., Maione, G. and Niu, Q. (2012) Bio-inspired computing and applications (LSMS-ICSEE, 2010). Neurocomputing, 98. pp. 1-3. ISSN 0925-2312 doi: https://doi.org/10.1016/j.neucom.2012.05.014

Gao, M., Hong, X., Chen, S. and Harris, C. J. (2011) A combined SMOTE and PSO based RBF classifier for two-class imbalanced problems. Neurocomputing, 74 (17). pp. 3456-3466. ISSN 0925-2312 doi: https://doi.org/10.1016/j.neucom.2011.06.010

Chen, S., Hong, X. and Harris, C. J. (2011) Grey-box radial basis function modelling. Neurocomputing, 74 (10). pp. 1564-1571. ISSN 0925-2312 doi: https://doi.org/10.1016/j.neucom.2011.01.023

Hong, X. and Chen, S. (2011) Modeling of complex-valued Wiener systems using B-spline neural network. IEEE Transactions on Neural Networks, 22 (5). pp. 818-825. ISSN 1045-9227 doi: https://doi.org/10.1109/TNN.2011.2119328

Chen, S., Hong, X. and Harris, C. J. (2010) Particle swarm optimization aided orthogonal forward regression for unified data modeling. IEEE Transactions on Evolutionary Computation, 14 (4). pp. 477-499. ISSN 1089-778X doi: https://doi.org/10.1109/TEVC.2009.2035921

Chen, S., Hong, X. and Harris, C. J. (2010) Probability density estimation with tunable kernels using orthogonal forward regression. IEEE Transactions on Systems Man and Cybernetics Part B-Cybernetics, 40 (4). pp. 1101-1114. ISSN 1083-4419 doi: https://doi.org/10.1109/TSMCB.2009.2034732

Chen, S., Hong, X. and Harris, C. J. (2010) Regression based D-optimality experimental design for sparse kernel density estimation. Neurocomputing, 73 (4-6). pp. 727-739. ISSN 0925-2312 doi: https://doi.org/10.1016/j.neucom.2009.11.002

Chen, S., Hong, X., Luk, B. L. and Harris, C. J. (2009) Construction of tunable radial basis function networks using orthogonal forward selection. IEEE Transactions on Systems Man and Cybernetics Part B-Cybernetics, 39 (2). pp. 457-466. ISSN 1083-4419 doi: https://doi.org/10.1109/tsmcb.2008.2006688

Chen, S., Harris, C. J., Hong, X. and Luk, B. L. (2009) Nonlinear system identification using particle swarm optimisation tuned radial basis function models. International Journal of Bio-Inspired Computation, 1 (4). pp. 246-257. ISSN 1758-0374 doi: https://doi.org/10.1504/IJBIC.2009.024723

Gong, Y. and Hong, X. (2009) OFDM joint data detection and phase noise cancellation based on minimum mean square prediction error. Signal Processing, 89 (4). pp. 502-509. ISSN 0165-1684 doi: https://doi.org/10.1016/j.sigpro.2008.10.006

Gong, Y. and Hong, X. (2009) OFDM joint data detection and phase noise cancellation for constant modulus modulations. IEEE Transactions on Signal Processing, 57 (7). pp. 2864-2868. ISSN 1053-587X doi: https://doi.org/10.1109/tsp.2009.2018362

Chen, S., Hong, X., Luk, B. L. and Harris, C. J. (2009) Orthogonal-least-squares regression: A unified approach for data modelling. Neurocomputing, 72 (10-12). pp. 2670-2681. ISSN 0925-2312 doi: https://doi.org/10.1016/j.neucom.2008.10.002

Hong, X. and Chen, S. (2009) A new RBF neural network with boundary value constraints. IEEE Transactions on Systems Man and Cybernetics Part B-Cybernetics, 39 (1). pp. 298-303. ISSN 1083-4419 doi: https://doi.org/10.1109/tsmcb.2008.2005124

Hong, X., Chen, S. and Harris, C. J. (2008) A-optimality orthogonal forward regression algorithm using branch and bound. IEEE Transactions on Neural Networks, 19 (11). pp. 1961-1967. ISSN 1045-9227 doi: https://doi.org/10.1109/tnn.2008.2003251

Chen, S., Hong, X., Harris, C. J. and Hanzo, L. (2008) Fully complex-valued radial basis function networks: orthogonal least squares regression and classification. Neurocomputing, 71 (16-18). pp. 3421-3433. ISSN 0925-2312 doi: https://doi.org/10.1016/j.neucom.2007.12.003

Li, K., Irwin, G. W. and Hong, X. (2008) Life system modelling, simulation, and bio-inspired computing (LSMS 2007). Neurocomputing, 72 (1-3). pp. 126-127. ISSN 0925-2312 doi: https://doi.org/10.1016/j.neucom.2008.08.001

Hong, X., Mitchell, R. J., Chen, S., Harris, C. J., Li, K. and Irwin, G. W. (2008) Model selection approaches for non-linear system identification: a review. International Journal of Systems Science, 39 (10). pp. 925-946. ISSN 0020-7721 doi: https://doi.org/10.1080/00207720802083018

Hong, X., Chen, S. and Harris, C. J. (2008) A fast linear-in-the-parameters classifier construction algorithm using orthogonal forward selection to minimize leave-one-out misclassification rate. International Journal of Systems Science, 39 (2). pp. 119-125. ISSN 0020-7721 doi: https://doi.org/10.1080/00207720701727822

Hong, X., Chen, S. and Harris, C. J. (2008) A forward-constrained regression algorithm for sparse kernel density estimation. IEEE Transactions on Neural Networks, 19 (1). pp. 193-198. ISSN 1045-9227 doi: https://doi.org/10.1109/tnn.2007.908645

Hong, X. and Chen, S. (2008) A minimum approximate-BER beamforming approach for PSK modulated wireless systems. International Journal of Automation and Computing, 5 (3). pp. 284-289. ISSN 1476-8186 doi: https://doi.org/10.1007/s11633-008-0284-8

Chen, S., Hong, X. and Harris, C. J. (2008) An orthogonal forward regression technique for sparse kernel density estimation. Neurocomputing, 71 (4-6). pp. 931-943. ISSN 0925-2312 doi: https://doi.org/10.1016/j.neucom.2007.02.008

Hong, X. and Mitchell, R. J. (2007) Backward elimination model construction for regression and classification using leave-one-out criteria. International Journal of Systems Science, 38 (2). pp. 101-113. ISSN 0020-7721 doi: https://doi.org/10.1080/00207720601051463

Hong, X. and Mitchell, R. J. (2007) Hammerstein model identification algorithm using Bezier-Bernstein approximation. IET Control Theory and Applications, 1 (4). pp. 1149-1159. ISSN 1751-8644 doi: https://doi.org/10.1049/iet-cta:20060018

Hong, X. (2007) Modified radial basis function neural network using output transformation. IET Control Theory and Applications, 1 (1). pp. 1-8. ISSN 1751-8644 doi: https://doi.org/10.1049/iet-cta:20050039

Zong, N. and Hong, X. (2007) A forward constrained selection algorithm for probabilistic neural network. Lecture Notes in Computer Science, 4492. pp. 699-704. ISSN 0302-9743 9783540723929

Hong, X., Chen, S. and Harris, C.J. (2007) A kernel-based two-class classifier for imbalanced data sets. IEEE Transactions on Neural Networks, 18 (1). pp. 28-41. ISSN 1045-9227 doi: https://doi.org/10.1109/TNN.2006.882812

Zong, N. and Hong, X. (2007) A multi-level probabilistic neural network. Lecture Notes in Computer Science, 4492. pp. 516-525. ISSN 0302-9743 9783540723929

Hong, X., Chen, S. and Harris, C. J. (2006) Fast kernel classifier construction using orthogonal forward selection to minimise leave-one-out misclassification rate. Lecture Notes in Computer Science, 4113. pp. 106-114. ISSN 0302-9743 9783540372714 doi: https://doi.org/10.1007/11816157_11

Hong, X. and Harwin, W.S. ORCID: https://orcid.org/0000-0002-3928-3381 (2006) Finding the point on Bezier Curves with the normal vector passing an external point. International Journal of Modelling Identification and Control, 1 (4). doi: https://doi.org/10.1504/IJMIC.2006.012620

Chen, S., Wang, X. X., Hong, X. and Harris, C. J. (2006) Kernel classifier construction using orthogonal forward selection and boosting with Fisher ratio class separability measure. IEEE Transactions on Neural Networks, 17 (6). pp. 1652-1656. ISSN 1045-9227 doi: https://doi.org/10.1109/tnn.2006.881487

Hong, X. (2006) A fast identification algorithm for Box-Cox transformation based radial basis function neural network. IEEE Transactions on Neural Networks, 17 (4). pp. 1064-1069. ISSN 1045-9227 doi: https://doi.org/10.1109/tnn.2006.875986

Chen, S., Hong, X., Harris, C. J. and Wang, X. X. (2005) Identification of nonlinear systems using generalized kernel models. IEEE Transactions on Control Systems Technology, 13 (3). pp. 401-411. ISSN 1063-6536 doi: https://doi.org/10.1109/tcst.2004.841652

Hong, X. and Chen, S. (2005) M-estimator, and D-optimality model construction using orthogonal forward regression. IEEE Transactions on Systems Man and Cybernetics Part B-Cybernetics, 35 (1). pp. 155-162. ISSN 1083-4419 doi: https://doi.org/10.1109/tsmcb.2004.839910

Zong, N. and Hong, X. (2005) Nonlinear channel equalizer design using directional evolutionary multi-objective optimization. International Journal of Systems Science, 36 (12). pp. 737-755. ISSN 0020-7721 doi: https://doi.org/10.1080/00207720500218908

Zong, N. and Hong, X. (2005) On improvement of classification accuracy for stochastic discrimination. IEEE Transactions on Systems Man and Cybernetics Part B-Cybernetics, 35 (1). pp. 142-149. ISSN 1083-4419 doi: https://doi.org/10.1109/tsmcb.2004.839908

Chen, S., Hong, X. and Harris, C. J. (2005) Orthogonal forward selection for constructing the radial basis function network with tunable nodes. Lecture Notes in Computer Science, 3644. pp. 777-786. ISSN 0302-9743

Hong, X., Chen, S. and Sharkey, P. M. (2004) Automatic Kernel Regression Modelling using Combined Leave-One-Out Test Score and Regularised Orthogonal Least Squares. International Journal of Neural Systems, 14 (1). pp. 27-37.

Hong, X., Brown, M. and Chen, S. (2004) Backward elimination methods for associative memory network pruning. International Journal of Hybrid Intelligent Systems, 1 (1-2). pp. 90-98.

Chen, S., Hong, X. and Harris, C. J. (2004) Kernel density construction using orthogonal forward regression. Lecture Notes in Computer Science, 3177. pp. 586-592. ISSN 0302-9743 3-540-22881-0

Hong, X., Harris, C. J. and Chen, S. (2004) Robust neurofuzzy rule base knowledge extraction and estimation using subspace decomposition combined with regularization and D-optimality. IEEE Transactions on Systems Man and Cybernetics Part B-Cybernetics, 34 (1). pp. 598-608. ISSN 1083-4419 doi: https://doi.org/10.1109/tsmcb.2003.817089

Chen, S., Hong, X. and Harris, C. J. (2004) Sparse kernel density construction using orthogonal forward regression with leave-one-out test score and local regularization. IEEE Transactions on Systems Man and Cybernetics Part B-Cybernetics, 34 (4). pp. 1708-1717. ISSN 1083-4419 doi: https://doi.org/10.1109/tsmcb.2004.828199

Hong, X., Brown, M., Chen, S. and Harris, C. J. (2004) Sparse model identification using orthogonal forward regression with basis pursuit and D-optimality. IEE Proceedings-Control Theory and Applications, 151 (4). pp. 491-498. ISSN 1350-2379 doi: https://doi.org/10.1049/ip-cta:20040693

Chen, S., Hong, X., Harris, C. J. and Sharkey, P. M. (2004) Sparse modeling using orthogonal forward regression with PRESS statistic and regularization. IEEE Transactions on Systems Man and Cybernetics Part B-Cybernetics, 34 (2). pp. 898-911. ISSN 1083-4419 doi: https://doi.org/10.1109/tsmcb.2003.817107

Hong, X., Sharkey, P. M. and Warwick, K. (2003) Automatic nonlinear predictive model-construction algorithm using forward regression and the PRESS statistic. IEE Proceedings-Control Theory and Applications, 150 (3). pp. 245-254. ISSN 1350-2379 doi: https://doi.org/10.1049/ip-cta:20030311

Hong, X. and Harris, C. J. (2003) Experimental design and model construction algorithms for radial basis function networks. International Journal of Systems Science, 34 (14-15). pp. 733-745. ISSN 0020-7721 doi: https://doi.org/10.1080/00207720310001640223

Hong, X., Harris, C. J., Chen, S. and Sharkey, P. M. (2003) Robust nonlinear model identification methods using forward regression. IEEE Transactions on Systems Man and Cybernetics Part A-Systems and Humans, 33 (4). pp. 514-523. ISSN 1083-4427 doi: https://doi.org/10.1109/tsmca.2003.809217

Chen, S., Hong, X. and Harris, C. J. (2003) Sparse kernel regression modeling using combined locally regularized orthogonal least squares and D-optimality experimental design. IEEE Transactions on Automatic Control, 48 (6). pp. 1029-1036. ISSN 0018-9286 doi: https://doi.org/10.1109/tac.2003.812790

Chen, S., Hong, X. and Harris, C. J. (2003) Sparse multioutput radial basis function network construction using combined locally regularised orthogonal least square and D-optimality experimental design. IEE Proceedings-Control Theory and Applications, 150 (2). pp. 139-146. ISSN 1350-2379 doi: https://doi.org/10.1049/ip-cta:20030253

Zong, N. and Hong, X. (2003) A combined algorithm using support vector machines and orthogonal forward regression with PRESS statistic. The 2003 UK Workshop on Computational Intelligence. pp. 315-319.

Wilson, P. A., Harris, C. J. and Hong, X. (2003) A line of sight counteraction navigation algorithm for ship encounter collision avoidance. Journal of Navigation, 56 (1). pp. 111-121.

Hong, X. and Harris, C. J. (2003) A neurofuzzy network knowledge extraction and extended gram-Schmidt algorithm for model subspace decomposition. IEEE Transactions on Fuzzy Systems, 11 (4). pp. 528-541. ISSN 1063-6706 doi: https://doi.org/10.1109/tfuzz.2003.814842

Hong, X., Brown, M., Harris, C.J. and Chen, S. (2003) An orthogonal forward regression algorithm combined with basis pursuit and D-optimality. IEEE SMC UK&RI Chapter Workshop: Cybernetic Intelligence-Challenges and Advances. pp. 57-62.

Hong, X., Sharkey, P. M. and Warwick, K. (2003) A robust nonlinear identification algorithm using PRESS statistic and forward regression. IEEE Transactions on Neural Networks, 14 (2). pp. 454-458. ISSN 1045-9227 doi: https://doi.org/10.1109/tnn.2003.809422

Hong, X. and Harris, C. J. (2002) Nonlinear model structure design and construction using orthogonal least squares and D-optimality design. IEEE Transactions on Neural Networks, 13 (5). pp. 1245-1250. ISSN 1045-9227 doi: https://doi.org/10.1109/TNN.2002.1031959

Hong, X. and Harris, C. J. (2002) A mixture of experts network structure construction algorithm for modelling and control. Applied Intelligence, 16 (1). pp. 59-69. ISSN 1573-7497 doi: https://doi.org/10.1023/A:1012869427428

Hong, X. and Harris, C. J. (2001) Neurofuzzy design and model construction of nonlinear dynamical processes from data. IEE Proceedings-Control Theory and Applications, 148 (6). pp. 530-538. ISSN 1350-2379 doi: https://doi.org/10.1049/ip-cta:20010704

Harris, C. J. and Hong, X. (2001) Neurofuzzy mixture of experts network parallel learning and model construction algorithms. IEE Proceedings-Control Theory and Applications, 148 (6). pp. 456-465. ISSN 1350-2379 doi: https://doi.org/10.1049/ip-cta:20010758

Hong, X. and Harris, C. J. (2001) Nonlinear model structure detection using optimum experimental design and orthogonal least squares. IEEE Transactions on Neural Networks, 12 (2). pp. 435-439. ISSN 1045-9227 doi: https://doi.org/10.1109/72.914539

Hong, X. and Harris, C. J. (2001) Variable selection algorithm for the construction of MIMO operating point dependent neurofuzzy networks. IEEE Transactions on Fuzzy Systems, 9 (1). pp. 88-101. ISSN 1063-6706 doi: https://doi.org/10.1109/91.917117

Harris, C. J. and Hong, X. (2001) Neurofuzzy control using Kalman filtering state feedback with coloured noise for unknown non-linear processes. Proceedings of the Institution of Mechanical Engineers, Part I: Journal of Systems and Control Engineering, 215 (5). pp. 423-435. ISSN 2041-3041 doi: https://doi.org/10.1177/095965180121500501

Hong, X. and Harris, C.J. (2000) Generalized neurofuzzy network modeling algorithms using Bezier-Bernstein polynomial functions and additive decomposition. IEEE Transactions on Neural Networks, 11 (4). pp. 889-902. ISSN 1045-9227 doi: https://doi.org/10.1109/72.857770

Harris, C.J. and Hong, X. (2000) Neurofuzzy network model construction using Bézier-Bernstein polynomial functions. IEE Proceedings-Control Theory and Applications, 147 (3). pp. 337-343. ISSN 1350-2379 doi: https://doi.org/10.1049/ip-cta:20000394

Hong, X. and Billings, S. A. (1999) Parameter estimation based on stacked regression and evolutionary algorithms. IEE Proceedings-Control Theory and Applications, 146 (5). pp. 406-414. ISSN 1350-2379 doi: https://doi.org/10.1049/ip-cta:19990505

Hong, X., Harris, C. J. and Wilson, P. A. (1999) Neurofuzzy state identification using prefiltering. IEE Proceedings-Control Theory and Applications, 146 (2). pp. 234-240. ISSN 1350-2379 doi: https://doi.org/10.1049/ip-cta:19990121

Hong, X. and Billings, S. A. (1999) Time series multistep-ahead predictability estimation and ranking. Journal of Forecasting, 18 (2). pp. 139-149. ISSN 0277-6693 doi: https://doi.org/10.1002/(SICI)1099-131X(199903)18:2<139::AID-FOR710>3.0.CO;2-W

Harris, C. J., Hong, X. and Wilson, P. A. (1999) An intelligent guidance and control system for ship obstacle avoidance. Proceedings of the Institution of Mechanical Engineers, Part I: Journal of Systems and Control Engineering, 213 (4). pp. 311-320. ISSN 2041-3041 doi: https://doi.org/10.1243/0959651991540179

Billings, S. A. and Hong, X. (1998) Dual-orthogonal radial basis function networks for nonlinear time series prediction. Neural Networks, 11 (3). pp. 479-493. ISSN 0893-6080 doi: https://doi.org/10.1016/S0893-6080(97)00132-9

Hong, X. and Billings, S.A. (1997) Givens rotation based fast backward elimination algorithm for RBF neural network pruning. IEE Proceedings-Control Theory and Applications, 144 (5). pp. 381-384. ISSN 1350-2379 doi: https://doi.org/10.1049/ip-cta:19971436

Book or Report Section

Xu, D., Fang, M., Hong, X. and Gao, J. (2019) Sparse least squares low rank kernel machines. In: International Conference on Neural Information Processing. Springer, Cham, pp. 395-406. ISBN 9783030367107 doi: https://doi.org/10.1007/978-3-030-36711-4_33

Fu, Y., Gao, J., Hong, X. and Tien, D. (2015) Low rank representation on Riemannian manifold of symmetric positive definite matrices. In: Proceedings of the 2015 SIAM International Conference on Data Mining. SIAM, pp. 316-324. ISBN 9781611974010 doi: https://doi.org/10.1137/1.9781611974010.36

Hong, X., Chen, S. and Harris, C. J. (2013) Complex-valued B-spline neural networks for modeling and inverse of Wiener systems. In: Hirose, A. (ed.) Complex-valued neural networks: advances and applications. Wiley-IEEE press, Hoboken, pp. 209-233. ISBN 9781118344606

Hong, X., Chen, S. and Harris, C. J. (2013) Complex-valued b-spline neural networks for modelling and inverse of wiener systems. In: Hirose, A. (ed.) Complex-Valued Neural Networks: Advances and Applications. John Wiley & Sons, Hoboken, NJ, pp. 209-233. doi: https://doi.org/10.1002/9781118590072.ch9

Guo, Y., Gao, J. B. and Hong, X. (2012) Constrained grouped sparsity. In: Thielscher, M. and Zhang, D. (eds.) AI 2012: Advances in Artificial Intelligence - Proceedings of the 25th Australasian Joint Conference. Lecture Notes in Computer Science (7691). Springer, pp. 433-444. ISBN 9783642351006 doi: https://doi.org/10.1007/978-3-642-35101-3_37

Gao, M., Hong, X. and Harris, C. J. (2012) A neurofuzzy classifier for two class problems. In: Proceedings of the UKCI 2012, the 12th UK Workshop on Computational Intelligence. Conference Publications. IEEE, pp. 1-6. ISBN 9781467343916 doi: https://doi.org/10.1109/UKCI.2012.6335763

Hong, X., Iplikci, S., Chen, S. and Warwick, K. (2012) B-spline neural networks based PID controller for Hammerstein systems. In: Huang, D.-S., Gupta, P., Zhang, X. and Premaratne, P. (eds.) Emerging Intelligent Computing Technology and Applications. Communications in Computer and Information Science, 304. Springer, pp. 38-46. doi: https://doi.org/10.1007/978-3-642-31837-5_6

Hong, X., Chen, S. and Harris, C. J. (2012) Construction of radial basis function networks with diversified topologies. In: Wang, L. and Garnier, H. (eds.) System identification, environmental modelling, and control system design. Springer, London, pp. 251-270. ISBN 9780857299734 doi: https://doi.org/10.1007/978-0-85729-974-1_13

Chen, S., Hong, X. and Harris, C. J. (2010) Radial basis function classifier construction using particle swarm optimisation aided orthogonal forward regression. In: The 2010 International Joint Conference on Neural Networks (IJCNN). IEEE, pp. 3418-3423. ISBN 9781424469161 doi: https://doi.org/10.1109/IJCNN.2010.5596855

Hong, X., Chen, S. and Harris, C. J. (2010) Sparse kernel density estimation technique based on zero-norm constraint. In: The 2010 International Joint Conference on Neural Networks (IJCNN). IEEE, pp. 3782-3787. ISBN 9781424469161 doi: https://doi.org/10.1109/IJCNN.2010.5596853

Hong, X. and Zhu, Q. M. (2009) An on-line algorithm of uncertain time delay estimation in a continuous system. In: 2009 IEEE International Conference on Networking, Sensing and Control, Vols 1 and 2. IEEE International Conference on Networking, Sensing and Control. IEEE, New York, pp. 498-501. ISBN 9781424434916

Gong, Y. and Hong, X. (2008) A new algorithm for OFDM joint data detection and phase noise cancellation. In: 2008 IEEE International Conference on Communications, Proceedings, Vols 1-13. IEEE International Conference on Communications. IEEE, New York, pp. 636-640. ISBN 1550-3607 9781424420742

Hong, X., Chen, S. and Harris, C. (2007) A sparse kernel density estimation algorithm using forward constrained regression. In: Huang, D. S., Heutte, L. and Loog, M. (eds.) Advanced Intelligent Computing Theories and Applications - with Aspects of Contemporary Intelligent Computing Techniques. Communications in Computer and Information Science, 2. Springer-Verlag Berlin, pp. 1354-1363. ISBN 9783540742814

Hong, X. and Harris, C.J. (2005) Neurofuzzy model construction, design and estimation. In: Ruano, A. E. (ed.) Intelligent Control Systems using Computational Intelligence Techniques. IEE Publishing, London UK, 219 - 252.

Zong, N. and Hong, X. (2004) Improvement of classification accuracy for stochastic discrimination - Multi-class classification. In: Chu, H. W., Savoie, M. and Sanchez, B. (eds.) International Conference on Computing, Communications and Control Technologies, Vol 2, Proceedings. Int Inst Informatics & Systemics, Orlando, pp. 17-22. ISBN 9806560175

Zong, N. and Hong, X. (2004) RBF equalizer design using directional evolutionary multi-objective optimization. In: Chu, H. W., Savoie, M., Toraichi, K. and Kwan, P. (eds.) International Conference on Computing, Communications and Control Technologies, Vol 3, Proceedings. Int Inst Informatics & Systemics, Orlando, pp. 109-114. ISBN 9806560175

Chen, S. and Hong, X. (2003) Orthogonal forward regression based on directly maximizing model generalization capability. In: Hu, H., Yue, Y. and Zhao, Z. (eds.) Proceedings of the 2003 Chinese automation & computing society conference in the UK 2003. Pacilantic International, pp. 251-256. ISBN 9780953389063

Hong, X., Harris, C. J., Chen, S. and Sharkey, P. M. (2003) Robust identification for linear-in-the-parameters models. In: Ruano, A. E., Ruano, M. G. and Fleming, P. J. (eds.) Intelligent Control Systems and Signal Processing 2003. Ifac Proceedings Series. Pergamon-Elsevier Science Ltd, Kidlington, pp. 273-278. ISBN 0080440886

Harris, C. J., Hong, X. and Gan, Q. (2000) Neurofuzzy state estimators. In: Sinha, N. K. and Gupta, M. M. (eds.) Soft computing and intelligent systems: theory and applications. Academic Press, pp. 377-402. ISBN 9780126464900

Hong, X., Harris, C. J. and Wilson, P. A. (1999) Autonomous ship collision free trajectory navigation and control algorithms. In: Proceedings of EFTA '99: the7th IEEE International Conference on Emerging Technologies and Factory Automation. IEEE Press, Barcelona, Spain, pp. 923-929. ISBN 0780356705 doi: https://doi.org/10.1109/ETFA.1999.813090

Conference or Workshop Item

Morris, J., Liu, Z., Liang, H., Nagala, S. and Hong, X. (2023) ThyExp: an explainable AI-assisted decision making toolkit for thyroid nodule diagnosis based on ultra-sound images. In: 32nd ACM International Conference on Information and Knowledge Management, Saturday 21 - Wednesday 25 October 2023, Birmingham,UK, pp. 5371-5375. doi: https://doi.org/10.1145/3583780.3615131

Osei-brefo, E., Mitchell, R. and Hong, X. (2023) Hybrid dual-resampling and cost-sensitive classification for credit risk prediction. In: AI-2023 Forty-third SGAI International Conference on Artificial Intelligence, 12-14 DECEMBER 2023, Cambridge, England. (In Press)

Amoudi, S. A., Hong, X. and Wei, H. (2022) Modified Probabilistic Neural Networks LBP Classification Based on Distance Measures in Probability Space. In: The 21st UK Workshop on Computational Intelligence, 7-9, Sept,2022, Sheffield. (In Press)

Hong, X., Wei, H. and Gao, J. (2020) Nonlinear logistic regression model based on simplex basis function. In: 2020 International Joint Conference on Neural Networks (IJCNN), 19-24 July 2020, Glasgow, United Kingdom (virtual). doi: https://doi.org/10.1109/IJCNN48605.2020.9207064

Alamoudi, S., Hong, X. and Wei, H. (2020) Plant leaf recognition using texture features and semi-supervised spherical K-means clustering. In: 2020 International Joint Conference on Neural Networks (IJCNN), 19-24 July 2020, Glasgow, United Kingdom (virtual). doi: https://doi.org/10.1109/IJCNN48605.2020.9207386

Moodley, P., Rosman, B. and Hong, X. (2019) Understanding structure of concurrent actions. In: AI-2019: The Thirty-ninth SGAI International Conference, 17-19 Dec 2019, Cambridge, UK, pp. 78-90.

Song, X., Jiang, X., Gao, J., Cai, Z. and Hong, X. (2018) Functional locality preserving projection for dimensionality reduction. In: 2018 International Joint Conference on Neural Networks (IJCNN), 8-13,July,2018, Rio.

Hong, X., Di Fatta, G., Chen, H. and Wang, S. (2018) Sparse least squares support vector regression for nonstationary systems. In: 2018 International Joint Conference on Neural Networks (IJCNN), 8-13 Jul 2018, Rio.

Chen, S., Hong, X., Khalaf, E., Alsaadi, F. E. and Harris, C. J. (2016) Complex-valued B-spline neural network and its application to iterative frequency-domain decision feedback equalization for Hammerstein communication systems. In: IJCNN 2016, 25-29, July, 2016, Vancouver.

Hong, X. and Junbin, G. (2016) A fast algorithm to estimate the square root of probability density function. In: AI2016, Thirty-sixth SGAI International Conference on Artificial Intelligence,, Dec,13-15, 2016 , Cambridge.

Hong, X. and Gao, J. (2016) Manifold optimization for nonnegative coefficient logistic regression. In: IJCNN 2016, 25-29, July, 2016, Vancouver.

Hong, X. and Gao, J. (2015) Sparse density estimation on multinomial manifold combining local component analysis. In: 2015 International Joint Conference on Neural Networks (IJCNN), 12-17, July, 2015, Killarney, Ireland.

Hong, X. and Gong, Y. (2015) A constrained recursive least squares algorithm for adaptive combination of multiple models. In: 2015 International Joint Conference on Neural Networks (IJCNN), 12-17, July, 2015, Killarney, Ireland.

Hong, X., Chen, S. and Harris, C. J. (2014) B-spline neural network based single-carrier frequency domain equalisation for Hammerstein channels. In: 2014 International Joint Conference on Neural Networks (IJCNN), July 6-11, 2014, Beijing, China.

Sun, Y., Gao, J., Hong, X., Guo, Y. and Harris, C. J. (2014) Dimensionality reduction assisted tensor clustering. In: 2014 International Joint Conference on Neural Networks (IJCNN), July 6-11, 2014, Beijing, China.

Jiang, X., Gao, J., Hong, X. and Cai, Z. (2014) Gaussian processes autoencoder for dimensionality reduction. In: Part II of Proceeding 18th Pacific-Asia Conference, PAKDD 2014, May 13-16, 2014, Tainan, Taiwan.

Fu, Y., Gao, J., Sun, Y. and Hong, X. (2014) Joint multiple dictionary learning for tensor sparse coding. In: 2014 International Joint Conference on Neural Networks (IJCNN), July 6-11, 2014., Beijing, China.

Chen, S., Hong, X. and Harris, C. J. (2014) On-line Gaussian mixture density estimator for adaptive minimum bit-error-rate beamforming receivers. In: 2014 International Joint Conference on Neural Networks (IJCNN), July 6-11, 2014, Beijing, China.

Fu, Y., Gao, J., Hong, X. and Tien, D. (2014) Tensor regression based on linked multiway parameter analysis. In: IEEE International Conference on Data Mining 2014, 14-17 Dec 2014, Shenzhen, China.

Hong, X., Guo, Y., Chen, S. and Gao, J. (2013) Sparse model construction using coordinate descent optimization. In: Proceedings: 18th International Conference on Digital Signal Processing (DSP2013), 1 - 3 July 2013, Santorini - Greece.

Hong, X. and Chen, S. (2013) A fast algorithm for sparse probability density function construction. In: 18th International Conference on Digital Signal Processing (DSP2013), 1 - 3 July 2013, Santorini - Greece.

Chen, H., Gong, Y. and Hong, X. (2012) Adaptive noise cancellation with fast tunable RBF network. In: SSPD 2012: Sensor Signal Processing for Defence, 25-27 September 2012, Imperial College, London.

Hong, X. and Chen, S. (2012) An elastic net orthogonal forward regression algorithm. In: 16th IFAC Symposium on System Identification, 11-13 July 2012, Brussels, Belgium, pp. 1814-1819.

Gao, M., Hong, X., Chen, S. and Harris, C. J. (2012) Probability density function estimation based over-sampling for imbalanced two-class problems. In: International Joint Conference on Neural Networks, 10-15 June 2012, Brisbane, Australia.

Hong, X., Chen, S. and Harris, C. J. (2012) Modelling and inverting complex-valued Wiener systems. In: International Joint Conference on Neural Networks, 10-15 June 2012, Brisbane, Australia.

Hong, X. and Chen, S. (2012) PSO assisted NURB Neural Network Identification. In: ICIC 2012: the Eighth International Conference on Intelligent Computing, 25-29 July 2012, Huangshan, China.

Hong, X., Mitchell, R. and Chen, S. (2011) Wiener System identification using B-spline functions with De Boor recursion. In: SSPD 2011: Sensor Signal Processing for Defence, 27-29 September 2011, Imperial College, London.

Gao, M., Hong, X., Chen, S. and Harris, C. J. (2011) On combination of SMOTE and particle swarm optimization based radial basis function classifier for imbalanced problems. In: IJCNN 2011, July 30th - August 5th, 2011, San Jose, CA,USA, pp. 1146-1153.

Chen, H., Gong, Y. and Hong, X. (2011) Adaptive modelling with tunable RBF network using multi-innovation RLS algorithm assisted by swarm intelligence. In: ICASSP'2011: the 36th International Conference on Acoustics, Speech and Signal Processing, 22-27 May 2011, Prague, Czech Republic, pp. 2132-2135.

Hong, X., Gong, Y. and Chen, S. (2011) B-spline neural network based digital baseband predistorter solution using the inverse of De Boor algorithm. In: International Joint Conference on Neural Networks (IJCNN 2011), 30 Jul - 5 Aug 2011, San Jose, California, USA, pp. 30-36.

Hong, X., Gong, Y. and Chen, S. (2011) A Wiener model for memory high power amplifiers using B-spline function approximation. In: 17th International Conference on Digital Signal Processing, 13-15 June 2011, Corfu, Greece. (ISBN: 9781457702730)

Gong, Y., Hong, X. and AbuSalem, K. (2010) Adaptive MMSE equalizer with optimum tap-length and decision delay. In: Sensor Signal Processing for Defence 2010 (SSPD 2010), 29-30 September 2010, Imperial College, London, UK.

Chen, S., Hong, X. and Harris, C.J. (2009) Grey-box radial basis function modelling: the art of incorporating prior knowledge. In: 15th Workshop on Statistical Signal Processing (SSP 2009) , Cardiff, Wales, UK . doi: https://doi.org/10.1109/SSP.2009.5278559

Chen, S., Hong, X., Luk, B. L. and Harris, C.J. (2009) A tunable radial basis function model for nonlinear system identification using particle swarm optimisation. In: 48th IEEE Conference on Decision and Control, held jointly with the 28th Chinese Control Conference (CDC/CCC 2009) , Shanghai, China, pp. 6762-6767. doi: https://doi.org/10.1109/CDC.2009.5399687

Chen, S., Hong, X. and Harris, C.J. (2008) Fully complex-valued radial basis function networks for orthogonal least squares regression. In: International Joint Conference on Neural Networks 2008 (IJCNN), Hong Kong, China. doi: https://doi.org/10.1109/IJCNN.2008.4633759

Chen, S., Hong, X. and Harris, C.J. (2008) Sparse kernel density estimator using orthogonal regression based on D-optimality experimental design. In: International Joint Conference on Neural Networks 2008 (IJCNN), Hong Kong, China. doi: https://doi.org/10.1109/IJCNN.2008.4633758

Chen, S., Hong, X. and Harris, C.J. (2007) Probability density function estimation using orthogonal forward regression. In: International Joint Conference on Neural Networks (IJCNN 2007), Orlando, USA. doi: https://doi.org/10.1109/IJCNN.2007.4371350

Chen, S., Hong, X. and Harris, C.J. (2007) Sparse kernel modelling: a unified approach. In: 8th International Conference on Intelligent Data Engineering and Automated Learning, Birmingham, UK.

Hong, X. and Mitchell, R.J. (2006) Bezier-Bernstein polynomial based Hammerstein model and identification algorithm - Paper ID23. In: International Control Conference, 30 Aug - 01 Sept 2006, Glasgow, United Kingdom.

Chen, S., Hong, X. and Harris, C.J. (2006) Construction of RBF classifiers with tunable units using orthonogal forward selection based on leave-one-out misclassification rate. In: Proceedings of 2006 International Joint Conference on Neural Networks, Vancouver, Canada, 6390 - 6394.

Hong, X. and Mitchell, R.J. (2006) A pole assignment controller for Bezier-Bernstein polynomial based Hammerstein model - Paper ID 95. In: Proc Control 2006, Glasgow, United Kingdom.

Hong, X. (2005) Identification of Box-Cox radial basis function neural network. In: Proc. of IFSA 2005 World Congress, Fuzzy Logic, Soft Computing and Computational Intelligence Theories and Applications, Beijing, China.

Chen, S., Hong, X., Wang, X.X. and Harris, C.J. (2005) Sparse generalised kernel modelling for nonlinear systems. In: Proc of the Joint 44th IEEE Conference on Decision and Control and European Control Conference (CDC-ECC'05), Seville, Spain.

Hong, X. and Chen, S. (2005) A forward regression algorithm based on M-estimators. In: Proc. of the 2005 WSEAS Int. Conf. on Dynamical Systems and Control, Venice, Italy.

Hong, X. (2005) A modified gradient descent nonlinear model parameter estimation algorithm by using combined micro-GA and constrained optimization. In: Proc. of IFSA 2005 World Congress, Fuzzy Logic, Soft Computing and Computational Intelligence Theories and Applications, Beijing, China.

Zong, N. and Hong, X. (2004) On improvement of classification accuracy for stochastic discrimination-multi-class Classification. In: Proc. Int. Conf. on Computing, Communications and Control Technologies, Austin, Texas.

Harris, C.J. and Hong, X. (2003) Neurofuzzy model construction and knowledge extraction using subspace decomposition. In: IFAC Conference on Intelligent Control and Signal Processing, Faro, Portugal.

Harris, C. J. and Hong, X. (2002) Neurofuzzy state space modelling and control using Kalman filtering state feedback with coloured noise. In: IFAC Adaptation and Learning in Control and Signal Processing (ALCOSP 2001), 29-31 Aug 2001, Como, Italy, pp502.

Chen, S., Hong, X. and Harris, C. J. (2002) Sparse data modelling using combined locally regularized orthogonal least squares and D-optimality design. In: CASIA & CACSUK 2002, 20-21 Sep 2002, Beijing, China.

Harris, C. J. and Hong, X. (2001) Neurofuzzy approaches to intelligent collision avoidance problems in (semi) autonomous transportation. In: Joint 9th IFSA World Congress and 20th NAFIPS International Conference: IFSA/NAFIPS 2001, 25-28 Jul 2001, Vancouver, Canada, pp. 517-522.

Harris, C. J. and Hong, X. (2001) Parallel neurofuzzy learning and construction algorithm. In: SPIE Applications and Science of Computational Intelligence IV 2001, 16-20 Apr 2001, Orlando, USA.

Harris, C. J. and Hong, X. (2000) Data based constructive identification - overcoming the curse of dimensionality. In: IFAC AIRTC symposium: Artificial Intelligence in Real Time Control, 2000, Budapest, Hungary.

Harris, C. J., Hong, X. and Feng, M. (1999) Optimal piecewise locally linear modeling. In: SPIE AeroSense'99, Applications and Science of Computational Intelligence II, 5th April 1999, Orlando, Florida, USA, p. 486. doi: https://doi.org/10.1117/12.342906

Harris, C. J., Hong, X. and Wilson, P. A. (1999) An intelligent guidance and control system for ship obstacle avoidance. In: CIMA/ISFL'99: International ICSC Conference on Computational Intelligence Methods and Applications, Fuzzy Logic and applications , 1999, Rochester, USA, pp. 135-140.

Book

Harris, C., Hong, X. and Gan, Q. (2002) Adaptive modelling, estimation and fusion from data: a neurofuzzy approach. Advanced Information Processing. Springer, Berlin, pp339. ISBN 9783540426868

This list was generated on Mon Mar 18 21:10:23 2024 UTC.

Page navigation