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Model-Based Signal Processing download epub

by James V. Candy


Epub Book: 1938 kb. | Fb2 Book: 1650 kb.

Model-Based Signal Processing develops the model-basedapproach in a unified manner and follows it through the text in thealgorithms, examples, applications, and case studies.

Model-Based Signal Processing develops the model-basedapproach in a unified manner and follows it through the text in thealgorithms, examples, applications, and case studies. The approach,coupled with the hierarchy of physics-based models that the authordevelops, including linear as well as nonlinear representations,makes it a unique contribution to the field of signalprocessing. The text includes parametric (. autoregressive or all-pole),sinusoidal, wave-based, and state-space models as some of the modelsets with its focus on how they may be used to solve signalprocessing problems.

Model-Based Signal Processing develops the model-based approach in a unified manner and follows it through the .

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.

Model-Based Signal Processing. The use of models in signal processing already plays a major role in the area of inverse problems, in which the goal is to extract information concerning the medium or certain of its contents. In such problems, the model plays the role of the structure in which the unknown parameters lie. Seismics is a good example of this.

Model-Based Signal Processing James V. Candy Wiley 9780471236320 : Model-BasSignal Processing . Candy Wiley 9780471236320 : Model-BasSignal Processing develops the model-based approach to signal processing for a variety of useful model sets includin. This book presents a unified treatment of the model-based approach and includes numerous case studies to demonstrate applicability of method to real-world situations, as well as MATLAB notes.

Model-Based Signal Processing develops the "model-based approach" to signal processing for a variety of useful model sets including . It presents a unique viewpoint of signal processing from the model-based perspective.

Model-Based Signal Processing develops the "model-based approach" to signal processing for a variety of useful model sets including the popularly termed "physics-based" models. A wide variety of case studies are included to demonstrate the applicability of the approach to real-world problems.

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.

This book takes the reader from the classical methods of model-based signal processing, t. .This is the first volume in a trilogy on modern Signal Processing. The three books provide.Bayesian Signal Processing. Indian Slow Cooker Cookbook: Top 100 Indian Slow Cooker Recipes from Restaurant Classics. 152 Pages·2016·621 KB·15,862 Downloads·New!

Model-Based Signal Processing. 1. 4 Mb. Model-Based Signal Processing.

Category: Образование. Category: science books, dsp digital signal processing.

Signal processing is based on this fundamental concept-the extraction of critical information from noisy, uncertain . The Bayesian approach is uniformly developed in this book's algorithms, examples, applications, and case studies.

Signal processing is based on this fundamental concept-the extraction of critical information from noisy, uncertain data.

James V. Candy Model-based signal processing incorporates the physical phenomena, measurements, and noise.

If signal levels are high, then basic techniques can be applied.

A unique treatment of signal processing using a model-basedperspectiveSignal processing is primarily aimed at extracting usefulinformation, while rejecting the extraneous from noisy data. Ifsignal levels are high, then basic techniques can be applied.However, low signal levels require using the underlying physics tocorrect the problem causing these low levels and extracting thedesired information. Model-based signal processing incorporates thephysical phenomena, measurements, and noise in the form ofmathematical models to solve this problem. Not only does theapproach enable signal processors to work directly in terms of theproblem's physics, instrumentation, and uncertainties, but itprovides far superior performance over the standard techniques.Model-based signal processing is both a modeler's as well as asignal processor's tool.Model-Based Signal Processing develops the model-based approach ina unified manner and follows it through the text in the algorithms,examples, applications, and case studies. The approach, coupledwith the hierarchy of physics-based models that the authordevelops, including linear as well as nonlinear representations,makes it a unique contribution to the field of signalprocessing.The text includes parametric (e.g., autoregressive or all-pole),sinusoidal, wave-based, and state-space models as some of the modelsets with its focus on how they may be used to solve signalprocessing problems. Special features are provided that assistreaders in understanding the material and learning how to applytheir new knowledge to solving real-life problems.* Unified treatment of well-known signal processing modelsincluding physics-based model sets* Simple applications demonstrate how the model-based approachworks, while detailed case studies demonstrate problem solutions intheir entirety from concept to model development, throughsimulation, application to real data, and detailed performanceanalysis* Summaries provided with each chapter ensure that readersunderstand the key points needed to move forward in the text aswell as MATLAB(r) Notes that describe the key commands andtoolboxes readily available to perform the algorithmsdiscussed* References lead to more in-depth coverage of specializedtopics* Problem sets test readers' knowledge and help them put their newskills into practiceThe author demonstrates how the basic idea of model-based signalprocessing is a highly effective and natural way to solve bothbasic as well as complex processing problems. Designed as agraduate-level text, this book is also essential reading forpracticing signal-processing professionals and scientists, who willfind the variety of case studies to be invaluable.

An Instructor's Manual presenting detailed solutions to all theproblems in the book is available from the Wiley editorialdepartment


Model-Based Signal Processing download epub
Networking & Cloud Computing
Author: James V. Candy
ISBN: 0471236322
Category: Computers & Technology
Subcategory: Networking & Cloud Computing
Language: English
Publisher: Wiley-IEEE Press; 1 edition (October 19, 2005)
Pages: 704 pages