Selection of a time-varying Volterra model using multiple hypothesis testing

Green, M.; Zoubir, Abdelhak M.

doi:10.1109/acssc.2000.911294

Cited by 2 publications

(1 citation statement)

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“…Thus the model may be reduces by discarding those packets that do not significantly contribute to the approximation. This may be done in several ways including multiple hypothesis testing [4], a model order selection criterion such as Akaike's Information Criterion or by simply by thresholding the coefficients.…”

Section: Wavelet Packetsmentioning

confidence: 99%

Selection of the best wavelet basis for a time-varying Volterra model

Green

Zoubir²

Conference Record of the Thirty-Fourth Asilomar Conference on Signals, Systems and Computers (Cat. No.00CH37154)

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To enable identification of a time-varying Volterra model using a single input/output realisation, sequences from an orthonormal basis are used to approximate the timevariation. Our work concerns the choice of sequencesfrom a library which comprises several bases. Using a library of wavelet packets allows-the use of the Best Basis algorithm. We apply the Best Basis algorithm in order to select the wavelet packets for approximating the true system's time-variation in the model. The minimum entropy criterion determines the most e@ient basis approximation enabling a minimum number of sequences to be used, leading to a more parsimonious model.

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Section: Wavelet Packetsmentioning

confidence: 99%