Abstract
This paper presents a utility of orthogonal wavelet transform in kurtosis-based blind deconvolution algorithm termed as EVA. In general, eigenvalues of the matrix at EVA issue are unchanged by an orthogonal transform alone. However, we note that wavelet transformation creates nearly lower triangle matrix. This utility promotes the faster convergence of well known power method in eigenvector calculation. We also present the potential applicability of this type of EVA in speech signal processing.
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