| 2008 |
|---|
| 44 | EE | Sheng Chen,
Xia Hong,
Chris J. Harris:
Sparse kernel density estimator using orthogonal regression based on D-Optimality experimental design.
IJCNN 2008: 1-6 |
| 43 | EE | 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 |
| 42 | EE | Sheng Chen,
Xia Hong,
Chris J. Harris:
Fully complex-valued radial basis function networks for orthogonal least squares regression.
IJCNN 2008: 7-12 |
| 41 | EE | 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) |
| 40 | EE | 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) |
| 39 | EE | 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) |
| 38 | EE | Sheng Chen,
Xia Hong,
Chris J. Harris:
An orthogonal forward regression technique for sparse kernel density estimation.
Neurocomputing 71(4-6): 931-943 (2008) |
| 2007 |
|---|
| 37 | EE | Sheng Chen,
Xia Hong,
Chris J. Harris:
Sparse Kernel Modelling: A Unified Approach.
IDEAL 2007: 27-36 |
| 36 | EE | Sheng Chen,
Andreas Wolfgang,
Chris J. Harris,
Lajos Hanzo:
Symmetric Kernel Detector for Multiple-Antenna Aided Beamforming Systems.
IJCNN 2007: 2486-2491 |
| 35 | EE | Sheng Chen,
Xia Hong,
Chris J. Harris:
Probability Density Function Estimation Using Orthogonal Forward Regression.
IJCNN 2007: 2492-2497 |
| 34 | EE | 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) |
| 2006 |
|---|
| 33 | EE | 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 |
| 32 | EE | 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 |
| 31 | EE | 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 |
|---|
| 30 | EE | 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 |
| 29 | EE | Sheng Chen,
Xunxian Wang,
Chris J. Harris:
A Search Algorithm for Global Optimisation.
ICNC (2) 2005: 1122-1130 |
| 28 | EE | Sheng Chen,
Xunxian Wang,
Chris J. Harris:
Experiments with repeating weighted boosting search for optimization signal processing applications.
IEEE Transactions on Systems, Man, and Cybernetics, Part B 35(4): 682-693 (2005) |
| 2004 |
|---|
| 27 | EE | Sheng Chen,
Xia Hong,
Chris J. Harris:
Kernel Density Construction Using Orthogonal Forward Regression.
IDEAL 2004: 586-592 |
| 26 | EE | 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) |
| 25 | EE | 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) |
| 24 | EE | 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) |
| 2003 |
|---|
| 23 | EE | Chris J. Harris:
Adaptive Data Based Modelling and Estimation with Application to Real Time Vehicular Collision Avoidance.
KES 2003: 13-14 |
| 22 | | 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) |
| 21 | EE | Junbin Gao,
Steve R. Gunn,
Chris J. Harris:
Mean field method for the support vector machine regression.
Neurocomputing 50: 391-405 (2003) |
| 20 | EE | Junbin Gao,
Steve R. Gunn,
Chris J. Harris:
SVM regression through variational methods and its sequential implementation.
Neurocomputing 55(1-2): 151-167 (2003) |
| 2002 |
|---|
| 19 | | Chris J. Harris,
Xia Hong,
Qiang Gan:
Adaptive Modelling, Estimation and Fusion from Data: A Neurofuzzy Approach
Springer 2002 |
| 18 | | Jang-Hee Yoo,
Mark S. Nixon,
Chris J. Harris:
Extraction and Description of Moving Human Body by Periodic Motion Analysis.
Computers and Their Applications 2002: 110-113 |
| 17 | | Jang-Hee Yoo,
Mark S. Nixon,
Chris J. Harris:
Model-driven statistical analysis of human gait motion.
ICIP (1) 2002: 285-288 |
| 16 | EE | Jang-Hee Yoo,
Mark S. Nixon,
Chris J. Harris:
Extracting Human Gait Signatures by Body Segment Properties.
SSIAI 2002: 35-39 |
| 15 | | Xia Hong,
Chris J. Harris:
A Mixture of Experts Network Structure Construction Algorithm for Modelling and Control.
Appl. Intell. 16(1): 59-69 (2002) |
| 14 | EE | Junbin Gao,
Chris J. Harris:
Some remarks on Kalman filters for the multisensor fusion.
Information Fusion 3(3): 191-201 (2002) |
| 13 | | Junbin Gao,
Steve R. Gunn,
Chris J. Harris,
Martin Brown:
A Probabilistic Framework for SVM Regression and Error Bar Estimation.
Machine Learning 46(1-3): 71-89 (2002) |
| 2001 |
|---|
| 12 | | M. Feng,
Chris J. Harris:
Piecewise Lyapunov stability conditions of fuzzy systems.
IEEE Transactions on Systems, Man, and Cybernetics, Part B 31(2): 259-262 (2001) |
| 11 | | Chris J. Harris,
Qiang Gan:
State estimation and multi-sensor data fusion using data-based neurofuzzy local linearisation process models.
Information Fusion 2(1): 17-29 (2001) |
| 10 | | Junbin Gao,
Chris J. Harris,
Steve R. Gunn:
On a Class of Support Vector Kernels Based on Frames in Function Hilbert Spaces.
Neural Computation 13(9): 1975-1994 (2001) |
| 2000 |
|---|
| 9 | EE | Jamie D. Shutler,
Mark S. Nixon,
Chris J. Harris:
Statistical Gait Description via Temporal Moments.
SSIAI 2000: 291-295 |
| 8 | EE | Chris J. Harris,
Junbin Gao:
Adaptive linear finite-element method for modelling nonlinear dynamic systems.
Int. J. System Science 31(10): 1241-1248 (2000) |
| 1999 |
|---|
| 7 | EE | Ping S. Huang,
Chris J. Harris,
Mark S. Nixon:
Recognising humans by gait via parametric canonical space.
AI in Engineering 13(4): 359-366 (1999) |
| 6 | | Qiang Gan,
Chris J. Harris:
Fuzzy local linearization and local basis function expansion in nonlinear system modeling.
IEEE Transactions on Systems, Man, and Cybernetics, Part B 29(4): 559-565 (1999) |
| 5 | | Qiang Gan,
Chris J. Harris:
Linearization and state estimation of unknown discrete-time nonlinear dynamic systems using recurrent neurofuzzy networks.
IEEE Transactions on Systems, Man, and Cybernetics, Part B 29(6): 802-817 (1999) |
| 1998 |
|---|
| 4 | EE | Ping S. Huang,
Chris J. Harris,
Mark S. Nixon:
Comparing Different Template Features for Recognizing People by their Gait.
BMVC 1998 |
| 3 | | 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 |
| 1997 |
|---|
| 2 | EE | Zhi Qiao Wu,
Chris J. Harris:
A neurofuzzy network structure for modelling and state estimation of unknown nonlinear systems.
Int. J. Systems Science 28(4): 335-345 (1997) |
| 1993 |
|---|
| 1 | EE | Martin Brown,
Chris J. Harris,
Patrick C. Parks:
The interpolation capabilities of the binary CMAC.
Neural Networks 6(3): 429-440 (1993) |
