Signals, Systems and Inference, Global Edition

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For upper-level undergraduate courses in deterministic and stochastic signals and system engineering, this comprehensive text builds on foundational courses in time- and frequency-domain analysis of signals and systems, as well as probability. Aimed at upper-level undergraduates and beginning graduate students in engineering and applied sciences, it pioneers a novel course of study that bridges introductory and advanced subjects. The text reviews properties and representations of deterministic signals and systems, covering group delay and state-space model behavior. It also introduces correlation functions and power spectral densities for 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. Emphasizing model-based approaches to inference, it addresses state estimation, signal estimation, and detection. The book explores concepts and tools relevant across various fields, including signal processing, control, communication, time-series analysis, financial engineering, and biomedicine. This flexible and long-awaited text is suitable for a rigorous course in a wide range of engineering and applied science curricula.