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Abstract

Most physical systems are conveniently modeled by a linear system. These include electrical circuits, mechanical machines, human biological functions, and chemical reactions, just to name a few. When the system is capable of responding to a continuous-time input, its effect can be described using a linear differential equation. For a system that responds to a discrete-time input a linear difference equation can be used to characterize the effect of the system. Furthermore, for systems whose characteristics do not change with time, the coefficients of the differential or difference equation are constants. Such a system is termed a linear time invariant (LTI) system for continuous-time inputs/outputs and a linear shift invariant (LSI) system for discrete-time inputs/outputs. In this chapter we explore the effect of these systems on wide sense stationary (WSS) random process inputs. The reader who is unfamiliar with the basic concepts of linear systems should first read Appendix D for a brief introduction. Many excellent books are available to supplement this material [Jackson 1991, Oppenheim, Willsky, and Nawab 1997, Poularikas and Seely 1985]. We will now consider only discrete-time systems and discrete-time WSS random processes. A summary of the analogous concepts for the continuous-time case is given in Section 18.6.

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© 2012 Steven M. Kay

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Kay, S.M. (2012). Linear Systems and Wide Sense Stationary Random Processes. In: Intuitive Probability and Random Processes Using MATLAB®. Springer, Boston, MA. https://doi.org/10.1007/0-387-24158-2_18

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  • DOI: https://doi.org/10.1007/0-387-24158-2_18

  • Publisher Name: Springer, Boston, MA

  • Print ISBN: 978-0-387-24157-9

  • Online ISBN: 978-0-387-24158-6

  • eBook Packages: EngineeringEngineering (R0)

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