A resource-allocating network for function interpolation
Neural Computation
Ten lectures on wavelets
Machine Learning
On-line Successive Synthesis of Wavelet Networks
Neural Processing Letters
Model selection in neural networks
Neural Networks
Unsupervised Feature Selection Using Feature Similarity
IEEE Transactions on Pattern Analysis and Machine Intelligence
Principles of Neural Model Identification, Selection and Adequacy: With Applications in Financial Econometrics
Foundations of Wavelet Networks and Applications
Foundations of Wavelet Networks and Applications
Neural-wavelet Methodology for Load Forecasting
Journal of Intelligent and Robotic Systems
Function Approximation Using Robust Wavelet Neural Networks
ICTAI '02 Proceedings of the 14th IEEE International Conference on Tools with Artificial Intelligence
On three intelligent systems: dynamic neural, fuzzy, and wavelet networks for training trajectory
Neural Computing and Applications
Feature Subset Selection and Ranking for Data Dimensionality Reduction
IEEE Transactions on Pattern Analysis and Machine Intelligence
Wavelet networks for nonlinear system modeling
Neural Computing and Applications
Prediction intervals for neural network models
ICCOMP'05 Proceedings of the 9th WSEAS International Conference on Computers
On a dynamic wavelet network and its modeling application
ICANN/ICONIP'03 Proceedings of the 2003 joint international conference on Artificial neural networks and neural information processing
Rough set approach for classification of breast cancer mammogram images
WILF'03 Proceedings of the 5th international conference on Fuzzy Logic and Applications
A constructive algorithm for wavelet neural networks
ICNC'05 Proceedings of the First international conference on Advances in Natural Computation - Volume Part I
Using wavelet network in nonparametric estimation
IEEE Transactions on Neural Networks
Multiwavelet neural network and its approximation properties
IEEE Transactions on Neural Networks
A new class of wavelet networks for nonlinear system identification
IEEE Transactions on Neural Networks
Analysis and synthesis of feedforward neural networks using discrete affine wavelet transformations
IEEE Transactions on Neural Networks
IEEE Transactions on Neural Networks
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Wavelet networks (WNs) are a new class of networks which have been used with great success in a wide range of applications. However a general accepted framework for applying WNs is missing from the literature. In this study, we present a complete statistical model identification framework in order to apply WNs in various applications. The following subjects were thoroughly examined: the structure of a WN, training methods, initialization algorithms, variable significance and variable selection algorithms, model selection methods and finally methods to construct confidence and prediction intervals. In addition the complexity of each algorithm is discussed. Our proposed framework was tested in two simulated cases, in one chaotic time series described by the Mackey-Glass equation and in three real datasets described by daily temperatures in Berlin, daily wind speeds in New York and breast cancer classification. Our results have shown that the proposed algorithms produce stable and robust results indicating that our proposed framework can be applied in various applications.