Subspace linear prediction approach to extracting poles

Yingbo Hua, Tapan Kumar Sarkar

Research output: Chapter in Book/Entry/PoemConference contribution

2 Scopus citations


It is shown that the conventioanl linear prediction (LP) methods (including various versions of the Prony method) and the matrix pencil method for extracting poles of data sequences can be unified under a generalized approach called subspace linear prediction (SLP) approach. The conventional LP methods can be considered as high-order SLP methods, while the matrix pencil method is a first-order SLP method. We also discuss a special form of the matrix pencil method for oversampled data. It is observed that, for oversampled data, the noise sensitivity of the least-square Prony method can be significantly improved without using singular value decomposition or other subspace decomposition algorithms.

Original languageEnglish (US)
Title of host publicationFourth Annu ASSP Workshop Spectrum Estim Model
PublisherIEEE Computer Society
Number of pages4
StatePublished - 1988

ASJC Scopus subject areas

  • General Engineering


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