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ORCIDChristopher J. Harris 0001
Chris J. Harris
Person information
- affiliation: Southampton University
Other persons with the same name
- Christopher J. Harris 0002 — SRI International (and 1 more)
- Christopher J. Harris 0003
![[0000-0001-6202-994X]](https://dblp.uni-trier.de./img/orcid-mark.12x12.png "0000-0001-6202-994X")
— University of Cambridge, Department of Economics, UK - Christopher J. Harris 0004 (aka: Chris Harris 0004) — Kitware Inc., Clifton Park, USA
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2020 – today
- 2024
[j101]Tong Liu, Sheng Chen, Po Yang, Yunpeng Zhu, Mehmet Mercangöz, Chris J. Harris:
Lifelong Learning Meets Dynamic Processes: An Emerging Streaming Process Prediction Framework With Delayed Process Output Measurement. IEEE Trans. Control. Syst. Technol. 32(2): 384-398 (2024)- [j100]Tong Liu, Xulong Wang, Po Yang, Sheng Chen, Chris J. Harris:
Unsupervised Transfer Aided Lifelong Regression for Learning New Tasks Without Target Output. IEEE Trans. Knowl. Data Eng. 36(9): 4981-4995 (2024) - 2023
- [j99]Tong Liu, Zeyue Tian, Sheng Chen, Kai Wang, Chris J. Harris:
Deep Cascade Gradient RBF Networks With Output-Relevant Feature Extraction and Adaptation for Nonlinear and Nonstationary Processes. IEEE Trans. Cybern. 53(8): 4908-4922 (2023) - [j98]Tong Liu, Sheng Chen, Kang Li, Shaojun Gan, Chris J. Harris:
Adaptive Multioutput Gradient RBF Tracker for Nonlinear and Nonstationary Regression. IEEE Trans. Cybern. 53(12): 7906-7919 (2023) - 2022
- [j97]Tong Liu, Sheng Chen, Shan Liang, Shaojun Gan, Chris J. Harris:
Multi-Output Selective Ensemble Identification of Nonlinear and Nonstationary Industrial Processes. IEEE Trans. Neural Networks Learn. Syst. 33(5): 1867-1880 (2022) - 2020
- [j96]Tong Liu, Sheng Chen, Shan Liang, Chris J. Harris:
Growing and Pruning Selective Ensemble Regression for Nonlinear and Nonstationary Systems. IEEE Access 8: 73278-73292 (2020) - [j95]Tong Liu, Sheng Chen, Shan Liang, Chris J. Harris:
Selective ensemble of multiple local model learning for nonlinear and nonstationary systems. Neurocomputing 378: 98-111 (2020) - [j94]Tong Liu, Sheng Chen, Shan Liang, Shaojun Gan, Chris J. Harris:
Fast Adaptive Gradient RBF Networks For Online Learning of Nonstationary Time Series. IEEE Trans. Signal Process. 68: 2015-2030 (2020)
2010 – 2019
- 2019
- [j93]Xiaogang Deng, Xuemin Tian, Sheng Chen, Chris J. Harris:
Deep Principal Component Analysis Based on Layerwise Feature Extraction and Its Application to Nonlinear Process Monitoring. IEEE Trans. Control. Syst. Technol. 27(6): 2526-2540 (2019) - [c43]Tong Liu, Shan Liang, Sheng Chen, Chris J. Harris:
A Multiple Local Model Learning for Nonlinear and Time-Varying Microwave Heating Process. IJCNN 2019: 1-8 - 2018
- [j92]Weiming Shao, Sheng Chen, Chris J. Harris:
Adaptive Soft Sensor Development for Multi-Output Industrial Processes Based on Selective Ensemble Learning. IEEE Access 6: 55628-55642 (2018) - [j91]Xiaogang Deng, Xuemin Tian, Sheng Chen, Chris J. Harris:
Nonlinear Process Fault Diagnosis Based on Serial Principal Component Analysis. IEEE Trans. Neural Networks Learn. Syst. 29(3): 560-572 (2018) - 2017
- [j90]Sheng Chen, Xia Hong, Emad Khalaf, Fuad E. Alsaadi, Chris J. Harris:
Comparative Performance of Complex-Valued B-Spline and Polynomial Models Applied to Iterative Frequency-Domain Decision Feedback Equalization of Hammerstein Channels. IEEE Trans. Neural Networks Learn. Syst. 28(12): 2872-2884 (2017) - [j89]Sheng Chen, Xia Hong, Emad Khalaf, Ali Morfeq, Naif D. Alotaibi, Chris J. Harris:
Single-Carrier Frequency-Domain Equalization With Hybrid Decision Feedback Equalizer for Hammerstein Channels Containing Nonlinear Transmit Amplifier. IEEE Trans. Wirel. Commun. 16(5): 3341-3354 (2017) - [c42]Xiaogang Deng, Xuemin Tian, Sheng Chen, Chris J. Harris:
Deep learning based nonlinear principal component analysis for industrial process fault detection. IJCNN 2017: 1237-1243 - 2016
- [c41]Sheng Chen, Xia Hong, Emad Khalaf, Fuad E. Alsaadi, Chris J. Harris:
Complex-valued B-spline neural network and its application to iterative frequency-domain decision feedback equalization for Hammerstein communication systems. IJCNN 2016: 4097-4104 - 2015
- [j88]Xia Hong, Sheng Chen, Junbin Gao, Chris J. Harris:
Nonlinear Identification Using Orthogonal Forward Regression With Nested Optimal Regularization. IEEE Trans. Cybern. 45(12): 2925-2936 (2015) - 2014
- [j87]Xia Hong, Junbin Gao, Xinwei Jiang, Chris J. Harris:
Fast identification algorithms for Gaussian process model. Neurocomputing 133: 25-31 (2014) - [j86]Ming Gao, Xia Hong, Sheng Chen, Chris J. Harris, Emad Khalaf:
PDFOS: PDF estimation based over-sampling for imbalanced two-class problems. Neurocomputing 138: 248-259 (2014) - [j85]Ming Gao, Xia Hong, Chris J. Harris:
A unified neurofuzzy model for classification. Int. J. Syst. Sci. 45(10): 2158-2171 (2014) - [j84]Ming Gao, Xia Hong, Chris J. Harris:
Construction of Neurofuzzy Models For Imbalanced Data Classification. IEEE Trans. Fuzzy Syst. 22(6): 1472-1488 (2014) - [j83]Sheng Chen, Xia Hong, Junbin Gao, Chris J. Harris:
Complex-Valued B-Spline Neural Networks for Modeling and Inverting Hammerstein Systems. IEEE Trans. Neural Networks Learn. Syst. 25(9): 1673-1685 (2014) - [j82]Xia Hong, Sheng Chen, Chris J. Harris, Emad Khalaf:
Single-Carrier Frequency Domain Equalization for Hammerstein Communication Systems Using Complex-Valued Neural Networks. IEEE Trans. Signal Process. 62(17): 4467-4478 (2014) - [j81]Xia Hong, Sheng Chen, Yu Gong, Chris J. Harris:
Nonlinear Equalization of Hammerstein OFDM Systems. IEEE Trans. Signal Process. 62(21): 5629-5639 (2014) - [c40]Yanfeng Sun, Junbin Gao, Xia Hong, Yi Guo, Chris J. Harris:
Dimensionality reduction assisted tensor clustering. IJCNN 2014: 1565-1572 - [c39]Xia Hong, Sheng Chen, Chris J. Harris:
B-spline neural network based single-carrier frequency domain equalisation for Hammerstein channels. IJCNN 2014: 1834-1841 - [c38]Sheng Chen, Xia Hong, Chris J. Harris:
On-line Gaussian mixture density estimator for adaptive minimum bit-error-rate beamforming receivers. IJCNN 2014: 3226-3233 - 2013
- [j80]Xia Hong, Junbin Gao, Sheng Chen, Chris J. Harris:
Particle swarm optimisation assisted classification using elastic net prefiltering. Neurocomputing 122: 210-220 (2013) - [j79]Sheng Chen, Xia Hong, Yu Gong, Chris J. Harris:
Digital Predistorter Design Using B-Spline Neural Network and Inverse of De Boor Algorithm. IEEE Trans. Circuits Syst. I Regul. Pap. 60-I(6): 1584-1594 (2013) - [j78]Xia Hong, Sheng Chen, Chris J. Harris:
Elastic-Net Prefiltering for Two-Class Classification. IEEE Trans. Cybern. 43(1): 286-295 (2013) - 2012
- [j77]Scott F. Page, Sheng Chen, Chris J. Harris, Neil M. White:
Repeated weighted boosting search for discrete or mixed search space and multiple-objective optimisation. Appl. Soft Comput. 12(9): 2740-2755 (2012) - [j76]Xia Hong, Sheng Chen, Chris J. Harris:
Using zero-norm constraint for sparse probability density function estimation. Int. J. Syst. Sci. 43(11): 2107-2113 (2012) - [c37]Ming Gao, Xia Hong, Sheng Chen, Chris J. Harris:
Probability density function estimation based over-sampling for imbalanced two-class problems. IJCNN 2012: 1-8 - [c36]Xia Hong, Sheng Chen, Chris J. Harris:
Modelling and inverting complex-valued wiener systems. IJCNN 2012: 1-8 - [c35]Ming Gao, Xia Hong, Chris J. Harris:
A neurofuzzy classifier for two class problems. UKCI 2012: 1-6 - 2011
- [j75]Sheng Chen, Xia Hong, Chris J. Harris:
Grey-box radial basis function modelling. Neurocomputing 74(10): 1564-1571 (2011) - [j74]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) - [c34]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 - 2010
- [j73]Sheng Chen, Bing Lam Luk, Chris J. Harris, Lajos Hanzo:
Fuzzy-logic tuned constant modulus algorithm and soft decision-directed scheme for blind equalisation. Digit. Signal Process. 20(3): 846-859 (2010) - [j72]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) - [j71]Sheng Chen, Xia Hong, Chris J. Harris:
Particle Swarm Optimization Aided Orthogonal Forward Regression for Unified Data Modeling. IEEE Trans. Evol. Comput. 14(4): 477-499 (2010) - [j70]Sheng Chen, Xia Hong, Chris J. Harris:
Probability Density Estimation With Tunable Kernels Using Orthogonal Forward Regression. IEEE Trans. Syst. Man Cybern. Part B 40(4): 1101-1114 (2010) - [c33]Sheng Chen, Xia Hong, Chris J. Harris:
Radial basis function classifier construction using particle swarm optimisation aided orthogonal forward regression. IJCNN 2010: 1-6 - [c32]Xia Hong, Sheng Chen, Chris J. Harris:
Sparse kernel density estimation technique based on zero-norm constraint. IJCNN 2010: 1-6
2000 – 2009
- 2009
- [j69]Sheng Chen, Xia Hong, Bing Lam Luk, Chris J. Harris:
Non-linear system identification using particle swarm optimisation tuned radial basis function models. Int. J. Bio Inspired Comput. 1(4): 246-258 (2009) - [j68]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) - [j67]Sheng Chen, Xia Hong, Bing Lam Luk, Chris J. Harris:
Construction of Tunable Radial Basis Function Networks Using Orthogonal Forward Selection. IEEE Trans. Syst. Man Cybern. Part B 39(2): 457-466 (2009) - [c31]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 - 2008
- [j66]Sheng Chen, Xia Hong, Chris J. Harris:
An orthogonal forward regression technique for sparse kernel density estimation. Neurocomputing 71(4-6): 931-943 (2008) - [j65]Sheng Chen, Xia Hong, Chris J. Harris, Lajos Hanzo:
Fully complex-valued radial basis function networks: Orthogonal least squares regression and classification. Neurocomputing 71(16-18): 3421-3433 (2008) - [j64]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. Syst. Sci. 39(2): 119-125 (2008) - [j63]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. Syst. Sci. 39(10): 925-946 (2008) - [j62]Sheng Chen, Andreas Wolfgang, Chris J. Harris, Lajos Hanzo:
Adaptive nonlinear least bit error-rate detection for symmetrical RBF beamforming. Neural Networks 21(2-3): 358-367 (2008) - [j61]Sheng Chen, Xunxian Wang, Chris J. Harris:
NARX-Based Nonlinear System Identification Using Orthogonal Least Squares Basis Hunting. IEEE Trans. Control. Syst. Technol. 16(1): 78-84 (2008) - [j60]Xia Hong, Sheng Chen, Chris J. Harris:
A Forward-Constrained Regression Algorithm for Sparse Kernel Density Estimation. IEEE Trans. Neural Networks 19(1): 193-198 (2008) - [j59]Sheng Chen, Andreas Wolfgang, Chris J. Harris, Lajos Hanzo:
Symmetric RBF Classifier for Nonlinear Detection in Multiple-Antenna-Aided Systems. IEEE Trans. Neural Networks 19(5): 737-745 (2008) - [j58]Xia Hong, Sheng Chen, Chris J. Harris:
A-Optimality Orthogonal Forward Regression Algorithm Using Branch and Bound. IEEE Trans. Neural Networks 19(11): 1961-1967 (2008) - [c30]Sheng Chen, Xia Hong, Chris J. Harris:
Sparse kernel density estimator using orthogonal regression based on D-Optimality experimental design. IJCNN 2008: 1-6 - [c29]Sheng Chen, Xia Hong, Chris J. Harris:
Fully complex-valued radial basis function networks for orthogonal least squares regression. IJCNN 2008: 7-12 - [c28]Sheng Chen, Chris J. Harris, Lajos Hanzo:
Complex-valued symmetric radial basis function classifier for quadrature phase shift keying beamforming systems. IJCNN 2008: 13-18 - 2007
- [j57]Alexander N. Dolia, Christopher J. Harris, John Shawe-Taylor, D. Mike Titterington:
Kernel ellipsoidal trimming. Comput. Stat. Data Anal. 52(1): 309-324 (2007) - [j56]Xia Hong, Sheng Chen, Chris J. Harris:
A Kernel-Based Two-Class Classifier for Imbalanced Data Sets. IEEE Trans. Neural Networks 18(1): 28-41 (2007) - [c27]Xia Hong, Sheng Chen, Chris J. Harris:
A Sparse Kernel Density Estimation Algorithm Using Forward Constrained Regression. ICIC (3) 2007: 1354-1363 - [c26]Sheng Chen, Xia Hong, Chris J. Harris:
Sparse Kernel Modelling: A Unified Approach. IDEAL 2007: 27-36 - [c25]Sheng Chen, Andreas Wolfgang, Chris J. Harris, Lajos Hanzo:
Symmetric Kernel Detector for Multiple-Antenna Aided Beamforming Systems. IJCNN 2007: 2486-2491 - [c24]Sheng Chen, Xia Hong, Chris J. Harris:
Probability Density Function Estimation Using Orthogonal Forward Regression. IJCNN 2007: 2492-2497 - 2006
- [j55]Xunxian Wang, Sheng Chen, Chris J. Harris:
Using the correlation criterion to position and shape RBF units for incremental modelling. Int. J. Autom. Comput. 3(4): 392-403 (2006) - [j54]Xunxian Wang, David Lowe, Sheng Chen, Chris J. Harris:
Parsimonious least squares support vector regression using orthogonal forward selection with the generalised kernel model. Int. J. Model. Identif. Control. 1(4): 245-256 (2006) - [j53]Xunxian Wang, Sheng Chen, David Lowe, Chris J. Harris:
Sparse support vector regression based on orthogonal forward selection for the generalised kernel model. Neurocomputing 70(1-3): 462-474 (2006) - [j52]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 Trans. Neural Networks 17(6): 1652-1656 (2006) - [c23]Scott F. Page, Alexander N. Dolia, Christopher J. Harris, Neil M. White:
Adaptive horizon model predictive control based sensor management for multi-target tracking. ACC 2006: 1-8 - [c22]Alexander N. Dolia, Tijl De Bie, Christopher J. Harris, John Shawe-Taylor, D. M. Titterington:
The Minimum Volume Covering Ellipsoid Estimation in Kernel-Defined Feature Spaces. ECML 2006: 630-637 - [c21]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 - [c20]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 - 2005
- [j51]Sheng Chen, Xia Hong, Chris J. Harris, Xunxian Wang:
Identification of nonlinear systems using generalized kernel models. IEEE Trans. Control. Syst. Technol. 13(3): 401-411 (2005) - [j50]Sheng Chen, Xunxian Wang, Chris J. Harris:
Experiments with repeating weighted boosting search for optimization signal processing applications. IEEE Trans. Syst. Man Cybern. Part B 35(4): 682-693 (2005) - [c19]Sheng Chen, Xia Hong, Xunxian Wang, Christopher J. Harris:
Sparse Generalized Kernel Modeling for Nonlinear Systems. CDC/ECC 2005: 2574-2579 - [c18]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 - [c17]Sheng Chen, Xunxian Wang, Chris J. Harris:
A Search Algorithm for Global Optimisation. ICNC (2) 2005: 1122-1130 - [p1]Jorge Axel Domínguez-López, Robert I. Damper, Richard M. Crowder, Christopher J. Harris:
Intelligent Neurofuzzy Control of a Robotic Gripper. Innovations in Robot Mobility and Control 2005: 155-199 - 2004
- [j49]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) - [j48]Jorge Axel Domínguez-López, Robert I. Damper, Richard M. Crowder, Christopher J. Harris:
Adaptive neurofuzzy control of a robotic gripper with on-line machine learning. Robotics Auton. Syst. 48(2-3): 93-110 (2004) - [j47]Xia Hong, Chris J. Harris, Sheng Chen:
Robust neurofuzzy rule base knowledge extraction and estimation using subspace decomposition combined with regularization and D-optimality. IEEE Trans. Syst. Man Cybern. Part B 34(1): 598-608 (2004) - [j46]Sheng Chen, Xia Hong, Chris J. Harris, Paul M. Sharkey:
Sparse modeling using orthogonal forward regression with PRESS statistic and regularization. IEEE Trans. Syst. Man Cybern. Part B 34(2): 898-911 (2004) - [j45]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 Trans. Syst. Man Cybern. Part B 34(4): 1708-1717 (2004) - [c16]Sheng Chen, Xia Hong, Chris J. Harris:
Kernel Density Construction Using Orthogonal Forward Regression. IDEAL 2004: 586-592 - [c15]Jorge Axel Domínguez-López, Richard M. Crowder, Robert I. Damper, Christopher J. Harris:
Adaptive neurofuzzy control of a robotic gripper with external disturbances. SMC (4) 2004: 3193-3198 - 2003
- [j44]Junbin Gao, Steve R. Gunn, Chris J. Harris:
Mean field method for the support vector machine regression. Neurocomputing 50: 391-405 (2003) - [j43]Junbin Gao, Steve R. Gunn, Chris J. Harris:
SVM regression through variational methods and its sequential implementation. Neurocomputing 55(1-2): 151-167 (2003) - [j42]Xia Hong, Chris J. Harris:
Experimental design and model construction algorithms for radial basis function networks. Int. J. Syst. Sci. 34(14-15): 733-745 (2003) - [j41]Sheng Chen, Xia Hong, Chris J. Harris:
Sparse kernel regression modeling using combined locally regularized orthogonal least squares and D-optimality experimental design. IEEE Trans. Autom. Control. 48(6): 1029-1036 (2003) - [j40]Xia Hong, Chris J. Harris:
A neurofuzzy network knowledge extraction and extended Gram-Schmidt algorithm for model subspace decomposition. IEEE Trans. Fuzzy Syst. 11(4): 528-541 (2003) - [j39]Shuzhi Sam Ge, Tong Heng Lee, Christopher J. Harris:
Adaptive neural network control for robotic manipulators [Book Review]. IEEE Trans. Robotics Autom. 19(3): 523-524 (2003) - [j38]Xia Hong, Chris J. Harris, Sheng Chen, Paul M. Sharkey:
Robust nonlinear model identification methods using forward regression. IEEE Trans. Syst. Man Cybern. Part A 33(4): 514-523 (2003) - [c14]Chris J. Harris:
Adaptive Data Based Modelling and Estimation with Application to Real Time Vehicular Collision Avoidance. KES 2003: 13-14 - 2002
- [b3]Chris J. Harris, Xia Hong, Qiang Gan:
Adaptive Modelling, Estimation and Fusion from Data: A Neurofuzzy Approach. Advanced information processing, Springer 2002, ISBN 3-540-42686-8, pp. I-XVI, 1-323 - [j37]Xia Hong, Chris J. Harris:
A Mixture of Experts Network Structure Construction Algorithm for Modelling and Control. Appl. Intell. 16(1): 59-69 (2002) - [j36]C. W. Chan, W. C. Chan, A. W. Jayawardena, Christopher J. Harris:
Structure selection of neurofuzzy networks based on support vector regression. Int. J. Syst. Sci. 33(9): 715-722 (2002) - [j35]Tony J. Dodd, Christopher J. Harris:
Identification of non-linear time series via kernels. Int. J. Syst. Sci. 33(9): 737-750 (2002) - [j34]Junbin Gao, Chris J. Harris:
Some remarks on Kalman filters for the multisensor fusion. Inf. Fusion 3(3): 191-201 (2002) - [j33]Junbin Gao, Steve R. Gunn, Chris J. Harris, Martin Brown:
A Probabilistic Framework for SVM Regression and Error Bar Estimation. Mach. Learn. 46(1-3): 71-89 (2002) - [j32]Sheng Chen, Steve R. Gunn, Chris J. Harris:
Errata to "The relevance vector machine technique for channel equalization application". IEEE Trans. Neural Networks 13(4): 1024 (2002) - [j31]Xia Hong, Chris J. Harris:
Nonlinear model structure design and construction using orthogonal least squares and D-optimality design. IEEE Trans. Neural Networks 13(5): 1245-1250 (2002) - [c13]Jang-Hee Yoo, Mark S. Nixon, Chris J. Harris:
Extraction and Description of Moving Human Body by Periodic Motion Analysis. CATA 2002: 110-113 - [c12]Jang-Hee Yoo, Mark S. Nixon, Chris J. Harris:
Model-driven statistical analysis of human gait motion. ICIP (1) 2002: 285-288 - [c11]Jang-Hee Yoo, Mark S. Nixon, Chris J. Harris:
Extracting Human Gait Signatures by Body Segment Properties. SSIAI 2002: 35-39 - 2001
- [j30]M. Feng, Chris J. Harris:
Feedback stabilization of fuzzy systems via linear matrix inequalities. Int. J. Syst. Sci. 32(2): 221-231 (2001) - [j29]Chris J. Harris, Qiang Gan:
State estimation and multi-sensor data fusion using data-based neurofuzzy local linearisation process models. Inf. Fusion 2(1): 17-29 (2001) - [j28]Junbin Gao, Chris J. Harris, Steve R. Gunn:
On a Class of Support Vector Kernels Based on Frames in Function Hilbert Spaces. Neural Comput. 13(9): 1975-1994 (2001) - [j27]Xia Hong, Chris J. Harris:
Variable selection algorithm for the construction of MIMO operating point dependent neurofuzzy networks. IEEE Trans. Fuzzy Syst. 9(1): 88-101 (2001) - [j26]Qiang Gan, Chris J. Harris:
A hybrid learning scheme combining EM and MASMOD algorithms for fuzzy local linearization modeling. IEEE Trans. Neural Networks 12(1): 43-53 (2001) - [j25]Xia Hong, Chris J. Harris:
Nonlinear model structure detection using optimum experimental design and orthogonal least squares. IEEE Trans. Neural Networks 12(2): 435-439 (2001) - [j24]Sheng Chen, Steve R. Gunn, Chris J. Harris:
The relevance vector machine technique for channel equalization application. IEEE Trans. Neural Networks 12(6): 1529-1532 (2001) - [j23]M. Feng, Chris J. Harris:
Piecewise Lyapunov stability conditions of fuzzy systems. IEEE Trans. Syst. Man Cybern. Part B 31(2): 259-262 (2001) - [c10]Jitendriya K. Satapathy, Christopher J. Harris:
A pseudo-adaptive fuzzy controller using hybrid T-operator concept. ISCAS (3) 2001: 604-607 - 2000
- [j22]Chris J. Harris:
Editor's Letter. Int. J. Syst. Sci. 31(1): 1 (2000) - [j21]Chris J. Harris, Junbin Gao:
Adaptive linear finite-element method for modelling nonlinear dynamic systems. Int. J. Syst. Sci. 31(10): 1241-1248 (2000) - [j20]Xia Hong, Christopher J. Harris:
Generalized neurofuzzy network modeling algorithms using Bezier-Bernstein polynomial functions and additive decomposition. IEEE Trans. Neural Networks Learn. Syst. 11(4): 889-902 (2000) - [c9]Sheng Chen, Chris J. Harris:
Design of the optimal separating hyperplane for the decision feedback equalizer using support vector machines. ICASSP 2000: 2701-2704 - [c8]Simon Feraday, Chris J. Harris, Kihong Shin, Mike Brennan, Malcolm Lindsay:
The Use of AI Methods for Evaluating Condition Dependent Dynamic Models of Vehicle Brake Squeal. IEA/AIE 2000: 46-55 - [c7]Jitendriya K. Satapathy, Susmita Das, Chris J. Harris, Pradeep Misra:
Indirect tuning of membership function in a fixed fuzzy structure for efficient control of a DC drive system. SMC 2000: 3790-3793 - [c6]Jamie D. Shutler, Mark S. Nixon, Chris J. Harris:
Statistical Gait Description via Temporal Moments. SSIAI 2000: 291-295
1990 – 1999
- 1999
- [j19]Ping S. Huang, Chris J. Harris, Mark S. Nixon:
Recognising humans by gait via parametric canonical space. Artif. Intell. Eng. 13(4): 359-366 (1999) - [j18]Kev M. Bossley, Martin Brown, Christopher J. Harris:
Neurofuzzy identification of an autonomous underwater vehicle. Int. J. Syst. Sci. 30(9): 901-913 (1999) - [j17]Qiang Gan, Chris J. Harris:
Fuzzy local linearization and local basis function expansion in nonlinear system modeling. IEEE Trans. Syst. Man Cybern. Part B 29(4): 559-565 (1999) - [j16]Qiang Gan, Chris J. Harris:
Linearization and state estimation of unknown discrete-time nonlinear dynamic systems using recurrent neurofuzzy networks. IEEE Trans. Syst. Man Cybern. Part B 29(6): 802-817 (1999) - [c5]Derek W. Long, Martin Brown, Christopher J. Harris:
Principal components in time-series modelling. ECC 1999: 1705-1710 - 1998
- [b2]Shuzhi Sam Ge, Tong Heng Lee, Christopher J. Harris:
Adaptive Neural Network Control of Robotic Manipulators. World Scientific Series in Robotics and Intelligent Systems 19, World Scientific 1998, ISBN 978-981-02-3452-2, pp. 1-396 - [j15]M. Feng, Chris J. Harris:
Adaptive neurofuzzy control for a class of state-dependent nonlinear processes. Int. J. Syst. Sci. 29(7): 759-771 (1998) - [c4]Ping S. Huang, Chris J. Harris, Mark S. Nixon:
Comparing Different Template Features for Recognizing People by their Gait. BMVC 1998: 1-10 - [c3]Ping S. Huang, Chris J. Harris, Mark S. Nixon:
A Statistical Approach for Recognizing Humans by Gait using Spatial-Temporal Templates. ICIP (3) 1998: 178-182 - [c2]Ping S. Huang, Chris J. Harris, Mark S. Nixon:
Recognizing humans by gait using a statistical approach for temporal templates. SMC 1998: 4556-4561 - 1997
- [j14]Zhi Qiao Wu, Chris J. Harris:
A neurofuzzy network structure for modelling and state estimation of unknown nonlinear systems. Int. J. Syst. Sci. 28(4): 335-345 (1997) - [j13]Pak Cheung Edgar An, Martin Brown, Chris J. Harris:
On the convergence rate performance of the normalized least-mean-square adaptation. IEEE Trans. Neural Networks 8(5): 1211-1214 (1997) - 1996
- [j12]Martin Brown, D. J. Mills, Christopher J. Harris:
The representation of fuzzy algorithms used in adaptive modelling and control schemes. Fuzzy Sets Syst. 79(1): 69-91 (1996) - [j11]Christopher J. Harris:
Editorial. Int. J. Syst. Sci. 27(2): 143-144 (1996) - [j10]Hong Wang, A. P. Wang, Martin Brown, Christopher J. Harris:
One-to-one mapping and its application to neural networks based control systems design. Int. J. Syst. Sci. 27(2): 161-170 (1996) - [j9]Christopher J. Harris:
Editorial Intelligent autonomous vehicles. Int. J. Syst. Sci. 27(8): 693 (1996) - [j8]Christopher J. Harris:
Editorial Robotic manipulators. Int. J. Syst. Sci. 27(11): 1065 (1996) - [j7]Pak Cheung Edgar An, Chris J. Harris:
An intelligent driver warning system for vehicle collision avoidance. IEEE Trans. Syst. Man Cybern. Part A 26(2): 254-261 (1996) - 1995
- [j6]Martin Brown, Christopher J. Harris:
A perspective and critique of adaptive neurofuzzy systems used for modelling and control applications. Int. J. Neural Syst. 6(2): 197-220 (1995) - [j5]Martin Brown, Chris J. Harris:
Comments on "Learning convergence in the cerebellar model articulation controller". IEEE Trans. Neural Networks 6(4): 1016-1018 (1995) - [j4]Pak Cheung Edgar An, Martin Brown, Chris J. Harris:
A global gradient-noise covariance expression for stationary real Gaussian inputs. IEEE Trans. Neural Networks 6(6): 1549-1551 (1995) - 1994
- [j3]Christopher J. Harris:
Neurocontrol : H. Tolle and E. Ersu. Autom. 30(11): 1810-1811 (1994) - [c1]D. J. Mills, Martin Brown, Christopher J. Harris:
Training Neurofuzzy Systems. AIRTC 1994: 191-196 - 1993
- [b1]Christopher J. Harris, Chris G. Moore, Martin Brown:
Intelligent Control - Aspects of Fuzzy Logic and Neural Nets. World Scientific Series in Robotics and Intelligent Systems 6, World Scientific 1993, ISBN 978-981-02-1042-7, pp. 1-400 - [j2]Martin Brown, Chris J. Harris, Patrick C. Parks:
The interpolation capabilities of the binary CMAC. Neural Networks 6(3): 429-440 (1993) - 1992
- [j1]Christopher J. Harris:
Fuzzy control & fuzzy systems : W. Pedrycz. Autom. 28(2): 443 (1992)
Coauthor Index
[j101] [j100] [j99] [j98] [j97] [j96] [j95] [j94] [j93] [c43] [j92] [j91] [j90] [j89] [c42] [c41] [j88] [j86] [j83] [j82] [j81] [c39] [c38] [j80] [j79] [j78] [j77] [j76] [c37] [c36] [j75] [j74] [c34] [j73] [j72] [j71] [j70] [c33] [c32] [j69] [j68] [j67] [c31] [j66] [j65] [j64] [j63] [j62] [j61] [j60] [j59] [j58] [c30] [c29] [c28] [j56] [c27] [c26] [c25] [c24] [j55] [j54] [j53] [j52] [c21] [c20] [j51] [j50] [c19] [c18] [c17] [j49] [j47] [j46] [j45] [c16] [j41] [j38] [j32] [j24] [c9]
[j90] [j89] [c41] [j88] [j87] [j86] [j85] [j84] [j83] [j82] [j81] [c40] [c39] [c38] [j80] [j79] [j78] [j76] [c37] [c36] [c35] [j75] [j74] [c34] [j72] [j71] [j70] [c33] [c32] [j69] [j68] [j67] [c31] [j66] [j65] [j64] [j63] [j60] [j58] [c30] [c29] [j56] [c27] [c26] [c24] [j52] [c21] [c20] [j51] [c19] [c18] [j49] [j47] [j46] [j45] [c16] [j42] [j41] [j40] [j38] [b3] [j37] [j31] [j27] [j25] [j20]
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