Abstract
In this and following two chapters, we will be concerned with detection of weak known, random, and composite signals in observations governed by the generalized noisy signal model proposed in Chapter 1, which accommodates multiplicative and signal-dependent noise as well as purely-additive noise. In particular, we will consider the locally optimum detection of known signals, based on the generalized version of the Neyman-Pearson fundamental lemma of statistical hypothesis testing in this chapter. Again, we will use the terms ’known signal’ and ’deterministic signal’ interchangeably in this book.
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© 2002 Springer-Verlag Berlin Heidelberg
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Song, I., Bae, J., Kim, S.Y. (2002). Locally Optimum Detection of Known Signals. In: Advanced Theory of Signal Detection. Signals and Communication Technology. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-04859-7_2
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DOI: https://doi.org/10.1007/978-3-662-04859-7_2
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-07708-1
Online ISBN: 978-3-662-04859-7
eBook Packages: Springer Book Archive