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Statistical Signal Processing

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  • First Online:
International Encyclopedia of Statistical Science

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Signal processing may broadly be considered to involve the recovery of information from physical observations. The received signals is usually disturbed by thermal, electrical, atmospheric or intentional interferences. Due to the random nature of the signal, statistical techniques play an important role in signal processing. Statistics is used in the formulation of appropriate models to describe the behavior of the system, the development of appropriate techniques for estimation of model parameters, and the assessment of model performances. Statistical Signal Processing basically refers to the analysis of random signals using appropriate statistical techniques. The main purpose of this article is to introduce different signal processing models and different statistical and computational issues involved in solving them.

The Multiple Sinusoids Model

The multiple sinusoids model may be expressed as

$$y(t) ={ \sum \limits _{k=1}^{M}}\{{A}_{ k}\cos ({\omega }_{k}t) + {B}_{k}\sin {\omega...

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References and Further Reading

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Author information

Authors and Affiliations

  1. Indian Institute of Technology Kanpur, Kanpur, India

    Debasis Kundu

Authors
  1. Debasis Kundu
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Editor information

Editors and Affiliations

  1. Department of Statistics and Informatics, Faculty of Economics, University of Kragujevac, City of Kragujevac, Serbia

    Miodrag Lovric

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Kundu, D. (2011). Statistical Signal Processing. In: Lovric, M. (eds) International Encyclopedia of Statistical Science. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-04898-2_552

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