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Titlebook: Coherence; In Signal Processing David Ramírez,Ignacio Santamaría,Louis Scharf Book 2022 The Editor(s) (if applicable) and The Author(s), un

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Some Nonlinear Evolution Equations,s whether or not the covariance matrices of independent vector-valued MVN models are equal. The chapter concludes with a discussion of the expected likelihood principle for cross-validating a covariance model.
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Alfonso Castro,Ratnasingham Shivajilized versions of CCA (KCCA) and the LMS adaptive filtering algorithm (KLMS). The chapter concludes with a discussion of a complex time-frequency distribution based on the coherence between a time series and its Fourier transform.
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Introduction,so serves to justify the use of complex signals, which will be extensive throughout the book, as well as to present the problem of extracting information from a multi-sensor array of series analysis that motivates our interest in coherence.
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Coherence and Classical Tests in the Multivariate Normal Model,s whether or not the covariance matrices of independent vector-valued MVN models are equal. The chapter concludes with a discussion of the expected likelihood principle for cross-validating a covariance model.
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Performance Bounds and Uncertainty Quantification,e Cramér-Rao bound for parameters that are carried in the mean value or the covariance matrix of a MVN model. Coherence arises naturally. A concluding section on information geometry ties the Cramér-Rao bound on error covariance to the resolvability of the underlying probability distribution from which measurements are drawn.
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