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Statistical Signal Processing

Nandini Kannan, Debasis Kundu

Abstract

Abstract Statistical signal processing is an important area of research with extensive applications in the fields of communication theory, array processing, seismology, and medical diagnosis. The goal of signal processing is to recover characteristics of the underlying process from observed data. The random nature of the signals underscores the need for statistical techniques in model formulation, estimation, and data analysis. A brief discussion of two models that have been widely studied in the signal processing literature is provided. In addition, different methods of estimation are presented, and some unique characteristics of these models are highlighted.

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Key concepts: Signal processing, Statistical signal processing, Computer science, SIGNAL (programming language), Multidimensional signal processing, Data processing, Statistical model, Array processing