Wavelet based non-parametric NARX models for nonlinear input-output system identification
International Journal of Systems Science
Adaptive fuzzy wavelet network control design for nonlinear systems
Fuzzy Sets and Systems
Orthogonal Least Squares Based on QR Decomposition for Wavelet Networks
ISNN '07 Proceedings of the 4th international symposium on Neural Networks: Part II--Advances in Neural Networks
ICANN '08 Proceedings of the 18th international conference on Artificial Neural Networks, Part I
A Miniature Robot System with Fuzzy Wavelet Basis Neural Network Controller
ICIC '08 Proceedings of the 4th international conference on Intelligent Computing: Advanced Intelligent Computing Theories and Applications - with Aspects of Artificial Intelligence
AIKED'09 Proceedings of the 8th WSEAS international conference on Artificial intelligence, knowledge engineering and data bases
WSEAS Transactions on Information Science and Applications
IEEE Transactions on Neural Networks
MQPSO based on wavelet neural network for network anomaly detection
WiCOM'09 Proceedings of the 5th International Conference on Wireless communications, networking and mobile computing
GA optimized wavelet neural networks
PRICAI'06 Proceedings of the 9th Pacific Rim international conference on Artificial intelligence
Numerical algorithm for non-linear systems identification based on wavelet transform
NMA'06 Proceedings of the 6th international conference on Numerical methods and applications
Nonlinear system identification using two-dimensional wavelet-based state-dependent parameter models
International Journal of Systems Science
Fuzzy wavelet neural network models for prediction and identification of dynamical systems
IEEE Transactions on Neural Networks
Novel FTLRNN with gamma memory for short-term and long-term predictions of chaotic time series
Applied Computational Intelligence and Soft Computing
Adaptive fuzzy wavelet neural controller design for chaos synchronization
Expert Systems with Applications: An International Journal
Adaptive wavelet neural controller design for a DC-DC power converter using an FPGA chip
WSEAS Transactions on Systems and Control
Expert Systems with Applications: An International Journal
Nonlinear identification of a PEM fuel cell humidifier using wavelet networks
ISNN'06 Proceedings of the Third international conference on Advances in Neural Networks - Volume Part III
A genetic algorithm for constructing wavelet neural networks
ICIC'06 Proceedings of the 2006 international conference on Intelligent Computing - Volume Part I
Engineering Applications of Artificial Intelligence
Orthogonal least squares based on singular value decomposition for spare basis selection
ISNN'10 Proceedings of the 7th international conference on Advances in Neural Networks - Volume Part I
Two Types of Haar Wavelet Neural Networks for Nonlinear System Identification
Neural Processing Letters
Hybrid adaptive wavelet-neuro-fuzzy system for chaotic time series identification
Information Sciences: an International Journal
Adaptive neural complementary sliding-mode control via functional-linked wavelet neural network
Engineering Applications of Artificial Intelligence
Wavelet neural networks: A practical guide
Neural Networks
Human lower extremity joint moment prediction: A wavelet neural network approach
Expert Systems with Applications: An International Journal
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A new class of wavelet networks (WNs) is proposed for nonlinear system identification. In the new networks, the model structure for a high-dimensional system is chosen to be a superimposition of a number of functions with fewer variables. By expanding each function using truncated wavelet decompositions, the multivariate nonlinear networks can be converted into linear-in-the-parameter regressions, which can be solved using least-squares type methods. An efficient model term selection approach based upon a forward orthogonal least squares (OLS) algorithm and the error reduction ratio (ERR) is applied to solve the linear-in-the-parameters problem in the present study. The main advantage of the new WN is that it exploits the attractive features of multiscale wavelet decompositions and the capability of traditional neural networks. By adopting the analysis of variance (ANOVA) expansion, WNs can now handle nonlinear identification problems in high dimensions.