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- W3023026515 abstract "Publisher SummaryDeconvolution is sometimes called systems identification. The subject of deconvolution is rich in theory and computational algorithms. This chapter provides an overview of the basic theory, physics, and computational algorithms associated with deconvolution. It reviews the essential components of deconvolution theory and a few computational algorithms. The chapter discusses an important concept encountered in the study of deconvolution, namely, minimum phase or minimum delay. It considers the deconvolution of linear time-invariant (LTI) systems with no measurement noise and the more difficult problem of the deconvolution of LTI systems that contain measurement noise. It also discusses the Levinson or Toeplitz recursion and its relationship to deconvolution and the deconvolution or inverse problem as it appears in speech and seismic signal processing. Although deconvolution is a general term, it has some specific practical applications. It is the core element in speech and seismic signal processing. Deconvolution defines the inverse problem. In speech, the forward problem is to produce the speech waveform from knowledge of the glottis excitation waveform and the vocal tract shape. The inverse problem for speech is to define the vocal tract shape from knowledge of the speech waveform and glottis excitation waveform. The chapter explains the way in which the theory of deconvolution is related to the inverse problem for speech." @default.
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- W3023026515 date "1987-01-01" @default.
- W3023026515 modified "2023-09-25" @default.
- W3023026515 title "Deconvolution" @default.
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- W3023026515 doi "https://doi.org/10.1016/b978-0-08-050780-4.50015-1" @default.
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