Journal ArticleDOI
Neural network adaptive wavelets for signal representation and classification
TLDR
The idea is introduced of a "super-wavelet," a linear combination of wavelets that itself is treated as a wavelet that allows the shape of the wavelet to adapt to a particular problem, which goes beyond adapting parameters of a fixed-shape wavelet.Abstract:
Methods are presented for adaptively generating wavelet templates for signal representation and classification using neural networks. Different network structures and energy functions are necessary and are given for representation and classification. The idea is introduced of a "super-wavelet," a linear combination of wavelets that itself is treated as a wavelet. The super-wavelet allows the shape of the wavelet to adapt to a particular problem, which goes beyond adapting parameters of a fixed-shape wavelet. Simulations are given for 1-D signals, with the concepts extendable to imagery. Ideas are discussed for applying the concepts in the paper to phoneme and speaker recognition.read more
Citations
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Journal ArticleDOI
Neural networks for classification: a survey
TL;DR: The issues of posterior probability estimation, the link between neural and conventional classifiers, learning and generalization tradeoff in classification, the feature variable selection, as well as the effect of misclassification costs are examined.
Journal ArticleDOI
Double Sparsity: Learning Sparse Dictionaries for Sparse Signal Approximation
TL;DR: The advantages of sparse dictionaries are discussed, and an efficient algorithm for training them are presented, and the advantages of the proposed structure for 3-D image denoising are demonstrated.
Journal ArticleDOI
Wavelet support vector machine
Li Zhang,Weida Zhou,Licheng Jiao +2 more
TL;DR: An admissible support vector (SV) kernel (the wavelet kernel), by which the feasibility and validity of wavelet support vector machines (WSVMs) in regression and pattern recognition are shown.
Journal ArticleDOI
Artificial intelligence techniques for sizing photovoltaic systems: A review
TL;DR: An overview of the AI-techniques for sizing photovoltaic (PV) systems: stand-alone PVs, grid-connected PV systems, PV-wind hybrid systems, etc.
Journal ArticleDOI
A new class of wavelet networks for nonlinear system identification
TL;DR: 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.
References
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Entropy-based algorithms for best basis selection
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Book
Phoneme recognition using time-delay neural networks
TL;DR: The authors present a time-delay neural network (TDNN) approach to phoneme recognition which is characterized by two important properties: using a three-layer arrangement of simple computing units, a hierarchy can be constructed that allows for the formation of arbitrary nonlinear decision surfaces, which the TDNN learns automatically using error backpropagation.
Journal ArticleDOI
Phoneme recognition using time-delay neural networks
TL;DR: In this article, the authors presented a time-delay neural network (TDNN) approach to phoneme recognition, which is characterized by two important properties: (1) using a three-layer arrangement of simple computing units, a hierarchy can be constructed that allows for the formation of arbitrary nonlinear decision surfaces, which the TDNN learns automatically using error backpropagation; and (2) the time delay arrangement enables the network to discover acoustic-phonetic features and the temporal relationships between them independently of position in time and therefore not blurred by temporal shifts in the input