Signals, systems & inference / Alan V. Oppenheim & George C. Verghese, Massachusetts Institute of Technology.
By: Oppenheim, Alan V
.
Contributor(s): Verghese, George C.
Harlow, Essex, England, UK : Pearson Education Limited, ©2017Edition: Global edition.Description: 604 pages : illustrations ; 24 cm.Content type: text ISBN: 9781292156200 (pbk).Other title: Signals, systems and inference.Subject(s): Signal processingDDC classification: 621.3822 Op52 2017 Other classification: COECS/E | Item type | Current location | Collection | Call number | Status | Date due | Barcode |
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College Library General Circulation Section | GC | GC 621.3822 Op52 2017 (Browse shelf) | Available | 84396 |
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| GC 621.3822 K96 ©2005. Digital signal processors: | GC 621.3822 M69 Digital signal processing: / | GC 621.3822 M69 2006 Digital signal processing: | GC 621.3822 Op52 2017 Signals, systems & inference / | GC 621.3822 Sch33 Fundamentals of digital signal processing using matlab / | GC 621.3822 T15 2019 Digital signal processing : | GC 621.38223 So44 Continuous and discrete signals and systems / |
Includes bibliographical references (pages 555-560) and index.
Signals and systems -- Amplitude, phase, and group delay -- Pulse amplitude modulation -- State space models -- LTI state space models -- State observers and state feedback -- Probabilistic models Estimation -- Hypothesis testing -- Random processes -- Power spectral density -- Signal estimation -- Signal detection
For upper-level undergraduate courses in deterministic and stochastic signals and system engineering. An Integrative Approach to Signals, Systems and Inference 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. The text explores ideas, methods and tools common to numerous fields involving signals, systems and inference: signal processing, control, communication, time-series analysis, financial engineering, biomedicine, and many others. Signals, Systems and Inference is a long-awaited and flexible text that can be used for a rigorous course in a broad range of engineering and applied science curricula.
College of Engineering and Computer Studies Bachelor of Science in Computer Engineering
Text in English
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