| | |
Univ. of Reading
List of publications from the DBLP Bibliography Server - FAQother persons with the same name:
- CSB - MetaPress - Google - Bing - Yahoo
 | 2012 | |
|---|---|---|
| 55 |      | Xia Hong, Sheng Chen: The system identification and control of Hammerstein system using non-uniform rational B-spline neural network and particle swarm optimization. Neurocomputing 82: 216-223 (2012) |
| 2011 | ||
| 54 | | Hao Chen, Yu Gong, Xia Hong: Adaptive modelling with tunable RBF network using multi-innovation RLS algorithm assisted by swarm intelligence. ICASSP 2011: 2132-2135 |
| 53 | | Ming Gao, Xia Hong, Sheng Chen, Chris J. Harris: On combination of SMOTE and particle swarm optimization based radial basis function classifier for imbalanced problems. IJCNN 2011: 1146-1153 |
| 52 | | Xia Hong, Yu Gong, Sheng Chen: B-spline neural network based digital baseband predistorter solution using the inverse of De Boor algorithm. IJCNN 2011: 30-36 |
| 51 | | Xia Hong, Sheng Chen: Modeling of Complex-Valued Wiener Systems Using B-Spline Neural Network. IEEE Transactions on Neural Networks 22(5): 818-825 (2011) |
| 50 | | Sheng Chen, Xia Hong, Chris J. Harris: Grey-box radial basis function modelling. Neurocomputing 74(10): 1564-1571 (2011) |
| 49 | | Ming Gao, Xia Hong, Sheng Chen, Chris J. Harris: A combined SMOTE and PSO based RBF classifier for two-class imbalanced problems. Neurocomputing 74(17): 3456-3466 (2011) |
| 2010 | ||
| 48 | | Sheng Chen, Xia Hong, Chris J. Harris: Radial basis function classifier construction using particle swarm optimisation aided orthogonal forward regression. IJCNN 2010: 1-6 |
| 47 | | Xia Hong, Sheng Chen, Chris J. Harris: Sparse kernel density estimation technique based on zero-norm constraint. IJCNN 2010: 1-6 |
| 46 | | Sheng Chen, Xia Hong, Chris J. Harris: Particle Swarm Optimization Aided Orthogonal Forward Regression for Unified Data Modeling. IEEE Trans. Evolutionary Computation 14(4): 477-499 (2010) |
| 45 | | Sheng Chen, Xia Hong, Chris J. Harris: Probability Density Estimation With Tunable Kernels Using Orthogonal Forward Regression. IEEE Transactions on Systems, Man, and Cybernetics, Part B 40(4): 1101-1114 (2010) |
| 44 | | Sheng Chen, Xia Hong, Chris J. Harris: Regression based D-optimality experimental design for sparse kernel density estimation. Neurocomputing 73(4-6): 727-739 (2010) |
| 2009 | ||
| 43 | | Sheng Chen, Xia Hong, Bing Lam Luk, Chris J. Harris: A tunable radial basis function model for nonlinear system identification using particle swarm optimisation. CDC 2009: 6762-6767 |
| 42 | | Yu Gong, Xia Hong: OFDM joint data detection and phase noise cancellation for constant modulus modulations. IEEE Transactions on Signal Processing 57(7): 2864-2868 (2009) |
| 41 | | Xia Hong, Sheng Chen: A New RBF Neural Network With Boundary Value Constraints. IEEE Transactions on Systems, Man, and Cybernetics, Part B 39(1): 298-303 (2009) |
| 40 | | Sheng Chen, Xia Hong, Bing Lam Luk, Chris J. Harris: Construction of Tunable Radial Basis Function Networks Using Orthogonal Forward Selection. IEEE Transactions on Systems, Man, and Cybernetics, Part B 39(2): 457-466 (2009) |
| 39 | | Sheng Chen, Xia Hong, Bing Lam Luk, Chris J. Harris: Non-linear system identification using particle swarm optimisation tuned radial basis function models. IJBIC 1(4): 246-258 (2009) |
| 38 | | Sheng Chen, Xia Hong, Bing Lam Luk, Chris J. Harris: Orthogonal-least-squares regression: A unified approach for data modelling. Neurocomputing 72(10-12): 2670-2681 (2009) |
| 37 | | Yu Gong, Xia Hong: OFDM joint data detection and phase noise cancellation based on minimum mean square prediction error. Signal Processing 89(4): 502-509 (2009) |
| 2008 | ||
| 36 | | Yu Gong, Xia Hong: A New Algorithm for OFDM Joint Data Detection and Phase Noise Cancellation. ICC 2008: 636-640 |
| 35 | | Sheng Chen, Xia Hong, Chris J. Harris: Sparse kernel density estimator using orthogonal regression based on D-Optimality experimental design. IJCNN 2008: 1-6 |
| 34 | | Sheng Chen, Xia Hong, Chris J. Harris: Fully complex-valued radial basis function networks for orthogonal least squares regression. IJCNN 2008: 7-12 |
| 33 | | Xia Hong, Sheng Chen, Chris J. Harris: A Forward-Constrained Regression Algorithm for Sparse Kernel Density Estimation. IEEE Transactions on Neural Networks 19(1): 193-198 (2008) |
| 32 | | Xia Hong, Sheng Chen, Chris J. Harris: A-Optimality Orthogonal Forward Regression Algorithm Using Branch and Bound. IEEE Transactions on Neural Networks 19(11): 1961-1967 (2008) |
| 31 | | Xia Hong, Richard J. Mitchell, Sheng Chen, Chris J. Harris, Kang Li, George W. Irwin: Model selection approaches for non-linear system identification: a review. Int. J. Systems Science 39(10): 925-946 (2008) |
| 30 | | Xia Hong, Sheng Chen, Chris J. Harris: A fast linear-in-the-parameters classifier construction algorithm using orthogonal forward selection to minimize leave-one-out misclassification rate. Int. J. Systems Science 39(2): 119-125 (2008) |
| 29 | | Sheng Chen, Xia Hong, Chris J. Harris: An orthogonal forward regression technique for sparse kernel density estimation. Neurocomputing 71(4-6): 931-943 (2008) |
| 28 | | Kang Li, Xia Hong, George W. Irwin: Life System Modelling, Simulation, and Bio-inspired Computing (LSMS 2007). Neurocomputing 72(1-3): 126-127 (2008) |
| 2007 | ||
| 27 | | Xia Hong, Sheng Chen, Chris J. Harris: A Sparse Kernel Density Estimation Algorithm Using Forward Constrained Regression. ICIC (3) 2007: 1354-1363 |
| 26 | | Sheng Chen, Xia Hong, Chris J. Harris: Sparse Kernel Modelling: A Unified Approach. IDEAL 2007: 27-36 |
| 25 | | Sheng Chen, Xia Hong, Chris J. Harris: Probability Density Function Estimation Using Orthogonal Forward Regression. IJCNN 2007: 2492-2497 |
| 24 | | Ning Zong, Xia Hong: A Multi-Level Probabilistic Neural Network. ISNN (2) 2007: 516-525 |
| 23 | | Ning Zong, Xia Hong: A Forward Constrained Selection Algorithm for Probabilistic Neural Network. ISNN (2) 2007: 699-704 |
| 22 | | Xia Hong, Sheng Chen, Chris J. Harris: A Kernel-Based Two-Class Classifier for Imbalanced Data Sets. IEEE Transactions on Neural Networks 18(1): 28-41 (2007) |
| 21 | | Xia Hong, R. J. Mitchell: Backward elimination model construction for regression and classification using leave-one-out criteria. Int. J. Systems Science 38(2): 101-113 (2007) |
| 2006 | ||
| 20 | | Xia Hong, Sheng Chen, Chris J. Harris: Fast Kernel Classifier Construction Using Orthogonal Forward Selection to Minimise Leave-One-Out Misclassification Rate. ICIC (1) 2006: 106-114 |
| 19 | | Sheng Chen, Chris J. Harris, Xia Hong: Construction of RBF Classifiers with Tunable Units using Orthogonal Forward Selection Based on Leave-One-Out Misclassification Rate. IJCNN 2006: 3358-3362 |
| 18 | | Xia Hong: A fast identification algorithm for box-cox transformation based radial basis function neural network. IEEE Transactions on Neural Networks 17(4): 1064-1069 (2006) |
| 17 | | Sheng Chen, Xunxian Wang, Xia Hong, Chris J. Harris: Kernel Classifier Construction Using Orthogonal Forward Selection and Boosting With Fisher Ratio Class Separability Measure. IEEE Transactions on Neural Networks 17(6): 1652-1656 (2006) |
| 2005 | ||
| 16 | | Sheng Chen, Xia Hong, Chris J. Harris: Orthogonal Forward Selection for Constructing the Radial Basis Function Network with Tunable Nodes. ICIC (1) 2005: 777-786 |
| 15 | | Ning Zong, Xia Hong: On improvement of classification accuracy for stochastic discrimination. IEEE Transactions on Systems, Man, and Cybernetics, Part B 35(1): 142-149 (2005) |
| 14 | | Xia Hong, Sheng Chen: M-estimator and D-optimality model construction using orthogonal forward regression. IEEE Transactions on Systems, Man, and Cybernetics, Part B 35(1): 155-162 (2005) |
| 2004 | ||
| 13 | | Sheng Chen, Xia Hong, Chris J. Harris: Kernel Density Construction Using Orthogonal Forward Regression. IDEAL 2004: 586-592 |
| 12 | | Sheng Chen, Xia Hong, Chris J. Harris, Paul M. Sharkey: Sparse modeling using orthogonal forward regression with PRESS statistic and regularization. IEEE Transactions on Systems, Man, and Cybernetics, Part B 34(2): 898-911 (2004) |
| 11 | | Sheng Chen, Xia Hong, Chris J. Harris: 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 34(4): 1708-1717 (2004) |
| 10 | | Xia Hong, Chris J. Harris, Martin Brown, Sheng Chen: Backward Elimination Methods for Associative Memory Network Pruning. Int. J. Hybrid Intell. Syst. 1(2): 90-98 (2004) |
| 9 | | Xia Hong, Sheng Chen, Paul M. Sharkey: Automatic Kernel Regression Modelling Using Combined Leave-One-Out Test Score and Regularised Orthogonal Least Squares. Int. J. Neural Syst. 14(1): 27-37 (2004) |
| 2003 | ||
| 8 | | Xia Hong, Paul M. Sharkey, Kevin Warwick: A robust nonlinear identification algorithm using PRESS statistic and forward regression. IEEE Transactions on Neural Networks 14(2): 454-458 (2003) |
| 7 | | Xia Hong, Chris J. Harris, Sheng Chen, Paul M. Sharkey: Robust nonlinear model identification methods using forward regression. IEEE Transactions on Systems, Man, and Cybernetics, Part A 33(4): 514-523 (2003) |
| 2002 | ||
| 6 |  | Chris J. Harris, Xia Hong, Qiang Gan: Adaptive Modelling, Estimation and Fusion from Data: A Neurofuzzy Approach Springer 2002 |
| 5 | | Xia Hong, Chris J. Harris: A Mixture of Experts Network Structure Construction Algorithm for Modelling and Control. Appl. Intell. 16(1): 59-69 (2002) |
| 4 | | Xia Hong, Chris J. Harris: Nonlinear model structure design and construction using orthogonal least squares and D-optimality design. IEEE Transactions on Neural Networks 13(5): 1245-1250 (2002) |
| 2001 | ||
| 3 | | Xia Hong, Chris J. Harris: Nonlinear model structure detection using optimum experimental design and orthogonal least squares. IEEE Transactions on Neural Networks 12(2): 435-439 (2001) |
| 2000 | ||
| 2 | | Xia Hong, Christopher J. Harris: Generalized neurofuzzy network modeling algorithms using Bezier-Bernstein polynomial functions and additive decomposition. IEEE Trans. Neural Netw. Learning Syst. 11(4): 889-902 (2000) |
| 1998 | ||
| 1 | | Stephen A. Billings, Xia Hong: Dual-orthogonal radial basis function networks for nonlinear time series prediction. Neural Networks 11(3): 479-493 (1998) |
| 1 | Stephen A. Billings (S. A. Billings) | [1] |
| 2 | Martin Brown | [10] |
| 3 | Hao Chen | [54] |
| 4 | Sheng Chen | [49] [52] [53] [55] |
| 5 | Sheng Chen | [7] [9] [10] [11] [12] [13] [14] [16] [17] [19] [20] [22] [25] [26] [27] [29] [30] [31] [32] [33] [34] [35] [38] [39] [40] [41] [43] [44] [45] [46] [47] [48] [50] [51] |
| 6 | Qiang Gan | [6] |
| 7 | Ming Gao | [49] [53] |
| 8 | Yu Gong | [36] [37] [42] [52] [54] |
| 9 | Chris J. Harris | [3] [4] [5] [6] [7] [10] [11] [12] [13] [16] [17] [19] [20] [22] [25] [26] [27] [29] [30] [31] [32] [33] [34] [35] [38] [39] [40] [43] [44] [45] [46] [47] [48] [49] [50] [53] |
| 10 | Christopher J. Harris | [2] |
| 11 | George W. Irwin | [28] [31] |
| 12 | Kang Li | [28] [31] |
| 13 | Bing Lam Luk | [38] [39] [40] [43] |
| 14 | R. J. Mitchell | [21] |
| 15 | Richard J. Mitchell | [31] |
| 16 | Paul M. Sharkey | [7] [8] [9] [12] |
| 17 | Xunxian Wang | [17] |
| 18 | Kevin Warwick | [8] |
| 19 | Ning Zong | [15] [23] [24] |
Colors in the list of coauthors
Last update Thu May 31 18:55:10 2012 CET by the DBLP Team —
Data released under the ODC-BY 1.0 license — See also our legal information page