ISBN: 9781260458930 - advanced signal processing: a concise guide (14 Ergebnisse)

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Paperback. Zustand: New. Publisher's Note: Products purchased from Third Party sellers are not guaranteed by the publisher for quality, authenticity, or access to any online entitlements included with the product.A comprehensive introduction to the mathematical principles and algorithms in statistical signal processing and modern neural networks. This text is an expanded version of a graduate course on advanced signal processing at the Johns Hopkins University Whiting school program for professionals with students from electrical engineering, physics, computer and data science, and mathematics backgrounds.  It covers the theory underlying applications in statistical signal processing including spectral estimation, linear prediction, adaptive filters, and optimal processing of uniform spatial arrays.  Unique among books on the subject, it also includes a comprehensive introduction to modern neural networks with examples in time series prediction and image classification.    Coverage includes:Mathematical structures of signal spaces and matrix factorizationslinear time-invariant systems and transformsLeast squares filtersRandom variables, estimation theory, and random processesSpectral estimation and autoregressive signal modelslinear prediction and adaptive filtersOptimal processing of linear arraysNeural networks.…

Paperback. Zustand: new. Paperback. Publisher's Note: Products purchased from Third Party sellers are not guaranteed by the publisher for quality, authenticity, or access to any online entitlements included with the product.A comprehensive introduction to the mathematical principles and algorithms in statistical signal processing and modern neural networks. This text is an expanded version of a graduate course on advanced signal processing at the Johns Hopkins University Whiting school program for professionals with students from electrical engineering, physics, computer and data science, and mathematics backgrounds. It covers the theory underlying applications in statistical signal processing including spectral estimation, linear prediction, adaptive filters, and optimal processing of uniform spatial arrays. Unique among books on the subject, it also includes a comprehensive introduction to modern neural networks with examples in time series prediction and image classification. Coverage includes:Mathematical structures of signal spaces and matrix factorizationslinear time-invariant systems and transformsLeast squares filtersRandom variables, estimation theory, and random processesSpectral estimation and autoregressive signal modelslinear prediction and adaptive filtersOptimal processing of linear arraysNeural networks "This is a core textbook on signal analysis and its underlying mathematics for upper undergraduate and graduate courses"-- Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.…

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Zustand: New. 2020. Concise. Hardcover. . . . . . Books ship from the US and Ireland.

Zustand: New. &Uumlber den AutorAmir-Homayoon Najmi, Ph.D., was a Fulbright scholar at the Relativity Centre, University of Texas. He has published research in wide areas including quantum field theory in cosmological space-times.

Paperback. Zustand: New. Publisher's Note: Products purchased from Third Party sellers are not guaranteed by the publisher for quality, authenticity, or access to any online entitlements included with the product.A comprehensive introduction to the mathematical principles and algorithms in statistical signal processing and modern neural networks. This text is an expanded version of a graduate course on advanced signal processing at the Johns Hopkins University Whiting school program for professionals with students from electrical engineering, physics, computer and data science, and mathematics backgrounds.  It covers the theory underlying applications in statistical signal processing including spectral estimation, linear prediction, adaptive filters, and optimal processing of uniform spatial arrays.  Unique among books on the subject, it also includes a comprehensive introduction to modern neural networks with examples in time series prediction and image classification.    Coverage includes:Mathematical structures of signal spaces and matrix factorizationslinear time-invariant systems and transformsLeast squares filtersRandom variables, estimation theory, and random processesSpectral estimation and autoregressive signal modelslinear prediction and adaptive filtersOptimal processing of linear arraysNeural networks.…