Signals, Systems and Inference

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9780133943283: Signals, Systems and Inference

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.

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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 in signals, systems, and probability. Catering to undergraduate and graduate students with a strong introductory background in engineering and applied science branches, this new textbook  pioneers a new course of study. In a departure from the usual progression from broad introductory to highly specialized subjects, this engaging and inclusive text creates a study track that proves interesting to applied science and engineering students. The result is a flexible course that can be used as both a rigorous undergraduate and introductory graduate course in a broad range of engineering subjects.  


An extensive text that touches on broad fields such as signal processing, control, communication, financial engineering, biomedicine, and various others, Signals, Systems, and Inference is the long-awaited next step in an all-inclusive engineering and applied science education.

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Book Description Pearson Education (US), United States, 2015. Hardback. Book Condition: New. 236 x 178 mm. Language: English . Brand New Book. 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. Bookseller Inventory # BZV9780133943283

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