Signal-adaptive decomposition of multicomponent signals

Khaled T. Assaleh; Richard J. Mammone

doi:10.1117/12.160441

1 November 1993 Signal-adaptive decomposition of multicomponent signals

Khaled T. Assaleh, Richard J. Mammone

Proceedings Volume 2027, Advanced Signal Processing Algorithms, Architectures, and Implementations IV; (1993) https://doi.org/10.1117/12.160441
Event: SPIE's 1993 International Symposium on Optics, Imaging, and Instrumentation, 1993, San Diego, CA, United States

Abstract

In this paper we present a new method for adaptively decomposing a multicomponent signal into its components. This method is based on fitting an autoregressive (AR) model to the short-time spectra of the signal. The AR parameters represent the coefficients of the linear predictive (LP) polynomial. The roots of this polynomial constitute a set of center frequencies and bandwidths that characterize the modes of the signal. The decomposition process is achieved by applying a time-varying filter bank to the original multicomponent signal. The characteristics of this filter bank are derived from a subset of the roots of the LP polynomial. We have developed a constraining algorithm to determine that subset based on the boundedness of the bandwidths, and the temporal continuity of the center frequencies of the components. We have applied the proposed decomposition method for the separation of the formants of speech signals.

Citation Download Citation

Khaled T. Assaleh and Richard J. Mammone "Signal-adaptive decomposition of multicomponent signals", Proc. SPIE 2027, Advanced Signal Processing Algorithms, Architectures, and Implementations IV, (1 November 1993); https://doi.org/10.1117/12.160441

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