Signals, systems & inference / Alan V. Oppenheim & George C. Verghese, Massachusetts Institute of Technology.
Material type: TextSeries: Prentice-Hall signal processing seriesPublisher: Boston : Pearson, [2016]Copyright date: ©2016Description: xxx, 573 pages : illustrations ; 24 cmContent type:- text
- unmediated
- volume
- 9780133943283
- 0133943283
- Signals, systems and inference
- 621.3822 23
- TK5102.9 .O673 2016
Item type | Current library | Call number | Copy number | Status | Date due | Barcode | |
---|---|---|---|---|---|---|---|
Book | City Campus City Campus Main Collection | 621.3822 OPP (Browse shelf(Opens below)) | 1 | Available | A555031B |
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621.3822 MIT Digital signal processing : a computer-based approach / | 621.3822 MOI Rudiments of signal processing and systems / | 621.3822 MOI Rudiments of signal processing and systems / | 621.3822 OPP Signals, systems & inference / | 621.3822 PHI Signals, systems, and transforms. | 621.3822 PRO Digital signal processing / | 621.3822 ROB Signals and systems : analysis using transform methods and MATLAB / |
Includes bibliographical references (pages 555-560) and index.
Preface -- The Cover -- Acknowledgments -- Prologue -- 1. Signals and Systems -- 2. Amplitude, Phase, and Group Delay -- 3. Pulse-Amplitude Modulation -- 4. State-Space Models -- 5. LTI State-Space Models -- 6. State Observers and State Feedback -- 7. Probabilistic Models -- 8. Estimation -- 9. Hypothesis Testing -- 10. Random Processes -- 11. Power Spectral Density -- 12. Signal Estimation -- 13. Signal Detection -- Bibliography -- Index.
"Signals, Systems and Inference is a comprehensive text that builds on introductory courses in time- and frequency-domain analysis of signals and systems, and in probability. Directed primarily to upper-level undergraduates and beginning graduate students in engineering and applied science branches, this new textbook pioneers a novel course of study. Instead of the usual leap from broad introductory subjects to highly specialized advanced subjects, this engaging and inclusive text creates a study track for a transitional course. Properties and representations of deterministic signals and systems are reviewed and elaborated on, including group delay and the structure and behavior of state-space models. The text also introduces and interprets correlation functions and power spectral densities for describing and processing random signals. Application contexts include pulse amplitude modulation, observer-based feedback control, optimum linear filters for minimum mean-square-error estimation, and matched filtering for signal detection. Model-based approaches to inference are emphasized, in particular for state estimation, signal estimation, and signal detection." --Publisher's website.
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