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Fundamentals of Statistical Signal Processing: Practical Algorithm Development, Volume III by Steven M. Kay

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Chapter 5. Signal Model Selection

5.1. Introduction

In Chapters 3 and 4 we described some useful models for a signal and noise, respectively. We now examine in detail how one decides upon a particular model to represent data that will be encountered in practice. In this chapter we discuss signal model selection, with noise model selection deferred to the next chapter. Since according to Webster’s dictionary a model is defined to be a mathematical description used for “guidance or imitation”, we should not expect to be able to choose the correct one. Indeed, an exact description does not exist, so that our goal is to select a model that is sufficiently accurate to satisfy our needs. Hence, we attempt to find a suitable approximation to reality ...

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