Model-based signal processing / (Record no. 73799)
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| 000 -LEADER | |
|---|---|
| fixed length control field | 07330nam a2201165 i 4500 |
| 001 - CONTROL NUMBER | |
| control field | 5238083 |
| 005 - DATE AND TIME OF LATEST TRANSACTION | |
| control field | 20220712205620.0 |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION | |
| fixed length control field | 151221s2005 njua ob 001 eng d |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER | |
| ISBN | 9780471732679 |
| -- | ebook |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER | |
| -- | |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER | |
| -- | paper |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER | |
| -- | electronic |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER | |
| -- | electronic |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER | |
| -- | electronic |
| 082 04 - CLASSIFICATION NUMBER | |
| Call Number | 621.382/2 |
| 100 1# - AUTHOR NAME | |
| Author | Candy, J. V., |
| 245 10 - TITLE STATEMENT | |
| Title | Model-based signal processing / |
| 300 ## - PHYSICAL DESCRIPTION | |
| Number of Pages | 1 PDF (xxi, 677 pages) : |
| 490 1# - SERIES STATEMENT | |
| Series statement | Adaptive and learning systems for signal processing, communications and control series ; |
| 505 0# - FORMATTED CONTENTS NOTE | |
| Remark 2 | 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. |
| 520 ## - SUMMARY, ETC. | |
| Summary, etc | 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. * 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 * Summaries provided with each chapter ensure that readers understand the key points needed to move forward in the text as well as MATLAB(r) Notes that describe the key commands and toolboxes readily available to perform the algorithms discussed * References lead to more in-depth coverage of specialized topics * 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. An Instructor's Manual presenting detailed solutions to all the problems in the book is available from the Wiley editorial department. |
| 650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| Subject | Signal processing |
| General subdivision | Digital techniques |
| 856 42 - ELECTRONIC LOCATION AND ACCESS | |
| Uniform Resource Identifier | https://ieeexplore.ieee.org/xpl/bkabstractplus.jsp?bkn=5238083 |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) | |
| Koha item type | eBooks |
| 264 #1 - | |
| -- | Hoboken, New Jersey : |
| -- | IEEE Press, |
| -- | c2006. |
| 264 #2 - | |
| -- | [Piscataqay, New Jersey] : |
| -- | IEEE Xplore, |
| -- | [2005] |
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| -- | Description based on PDF viewed 12/21/2015. |
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