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Model-Based Signal Processing

Model-Based Signal Processing

Autorzy
Wydawnictwo John Wiley & Sons Inc
Data wydania 2005
Liczba stron 704
Forma publikacji książka w twardej oprawie
Poziom zaawansowania Dla profesjonalistów, specjalistów i badaczy naukowych
Język angielski
ISBN 9780471236320
Kategorie Inżynieria komunikacyjna i telekomunikacyjna
992.25 PLN (z VAT)
$223.20 / €212.74 / £184.68 /
Produkt na zamówienie
Dostawa 5-6 tygodni
Ilość
Do schowka

Opis książki

This book contains a unique treatment of signal processing using a model-based perspective. Signal processing is primarily aimed at extracting useful information, while rejecting the extraneous from noisy data. If signal levels are high, then basic techniques can be applied. However, low signal levels require using the underlying physics to correct the problem causing these low levels and extracting the desired information. Model-based signal processing incorporates the physical phenomena, measurements, and noise in the form of mathematical models to solve this problem. Not only does the approach enable signal processors to work directly in terms of the problem's physics, instrumentation, and uncertainties, but it provides far superior performance over the standard techniques. Model-based signal processing is both a modeler's as well as a signal processor's tool. "Model-Based Signal Processing" develops the model-based approach in a unified manner and follows it through the text in the algorithms, examples, applications, and case studies.
The approach, coupled with the hierarchy of physics-based models that the author develops, including linear as well as nonlinear representations, makes it a unique contribution to the field of signal processing. The text includes parametric (e.g., autoregressive or all-pole), sinusoidal, wave-based, and state-space models as some of the model sets with its focus on how they may be used to solve signal processing problems. Special features are provided that assist readers in understanding the material and learning how to apply their new knowledge to solving real-life problems. This book provides a unified treatment of well-known signal processing models including physics-based model sets. Simple applications demonstrate how the model-based approach works, while detailed case studies demonstrate problem solutions in their entirety from concept to model development, through simulation, application to real data, and detailed performance analysis. The summaries provided with each chapter ensure that readers understand the key points needed to move forward in the text as well as MATLAB[registered].
It includes notes that describe the key commands and toolboxes readily available to perform the algorithms discussed. The references lead to more in-depth coverage of specialized topics. The problem sets test readers' knowledge and help them put their new skills into practice. The author demonstrates how the basic idea of model-based signal processing is a highly effective and natural way to solve both basic as well as complex processing problems. Designed as a graduate-level text, this book is also essential reading for practicing signal-processing professionals and scientists, who will find the variety of case studies to be invaluable. "Given its extensive, but very cohesive and accessible coverage...this book could be very well appreciated by both students and specialists in the field." (Computing Reviews.com, August 1, 2006) "...belongs in the library of every practicing signal processor." (Journal of the Acoustical Society of America, May 2006)

Model-Based Signal Processing

Spis treści

Preface. Acknowledgments. 1. Introduction. 2. Discrete Random Signals ans Systems. 3. Estimation Theory. 4. AR, MA, ARMAX, Lattice, Exponential, Wave Model-Based Processors. 5. Linear State-Space Model-Based Processors. 6. Nonlinear State-Space Model-Based Processors. 7. Adaptive AR, MA, ARMAX, Exponential Model-Based Processors. 8. Adaptive State-Space Model-Based Processors. 9. Applied Physics-Based Processors. Appendix A: Probability and Statistics Overview. Appendix B: Sequential MBP and UD-Factorization. Appendix C: SSpack-PC: An Interactive Model-Based Processing Software Package. Index.

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