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Signals, Systems and Inference by George Verghese and Alan Oppenheim (2015, Hardcover)

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About this product

Product Identifiers

PublisherPearson Education

ISBN-100133943283

ISBN-139780133943283

eBay Product ID (ePID)210341372

Product Key Features

Number of Pages608 Pages

LanguageEnglish

Publication NameSignals, Systems and Inference

Publication Year2015

SubjectSignals & Signal Processing, Electrical

TypeTextbook

Subject AreaTechnology & Engineering

AuthorGeorge Verghese, Alan Oppenheim

FormatHardcover

Dimensions

Item Height1.1 in

Item Weight36.7 Oz

Item Length9.4 in

Item Width7.2 in

Additional Product Features

Intended AudienceCollege Audience

LCCN2014-043376

Dewey Edition23

IllustratedYes

Dewey Decimal621.382/2

Table Of ContentPreface The Cover Acknowledgments Prologue 1. Signals and Systems 1.1 Signals, Systems, Models, and Properties 1.1.1 System Properties 1.2 Linear, Time-Invariant Systems 1.2.1 Impulse-Response Representation of LTI Systems 1.2.2 Eigenfunction and Transform Representation of LTI Systems 1.2.3 Fourier Transforms 1.3 Deterministic Signals and Their Fourier Transforms 1.3.1 Signal Classes and Their Fourier Transforms 1.3.2 Parseval''s Identity, Energy Spectral Density, and Deterministic Autocorrelation 1.4 Bilateral Laplace and Z-Transforms 1.4.1 The Bilateral z-Transform 1.4.2 The Bilateral Laplace Transform 1.5 Discrete-Time Processing of Continuous-Time Signals 1.5.1 Basic Structure for DT Processing of CT Signals 1.5.2 DT Filtering and Overall CT Response 1.5.3 Nonideal D/C Converters 1.6 Further Reading Problems Basic Problems Advanced Problems Extension Problems 2. Amplitude, Phase, and Group Delay 2.1 Fourier Transform Magnitude and Phase 2.2 Group Delay and the Effect of Nonlinear Phase 2.2.1 Narrowband Input Signals 2.2.2 Broadband Input Signals 2.3 All-Pass and Minimum-Phase Systems 2.3.1 All-Pass Systems 2.3.2 Minimum-Phase Systems 2.3.3 The Group Delay of Minimum-Phase Systems 2.4 Spectral Factorization 2.5 Further Reading Problems Basic Problems Advanced Problems Extension Problems 3. Pulse-Amplitude Modulation 3.1 Baseband Pulse-Amplitude Modulation 3.1.1 The Transmitted Signal 3.1.2 The Received Signal 3.1.3 Frequency-Domain Characterizations 3.1.4 Intersymbol Interference at the Receiver 3.2 Nyquist Pulses 3.3 Passband Pulse-Amplitude Modulation 3.3.1 Frequency-Shift Keying (FSK) 3.3.2 Phase-Shift Keying (PSK) 3.3.3 Quadrature-Amplitude Modulation (QAM) 3.4 Further Reading Problems Basic Problems Advanced Problems Extension Problems 4. State-Space Models 4.1 System Memory 4.2 Illustrative Examples 4.3 State-Space Models 4.3.1 DT State-Space Models 4.3.2 CT State-Space Models 4.3.3 Defining Properties of State-Space Models 4.4 State-Space Models from LTI Input-Output Models 4.5 Equilibria and Linearization of Nonlinear State-Space Models 4.5.1 Equilibrium 4.5.2 Linearization 4.6 Further Reading Problems Basic Problems Advanced Problems Extension Problems 5. LTI State-Space Models 5.1 Continuous-Time and Discrete-Time LTI Models 5.2 Zero-Input Response and Modal Representation 5.2.1 Undriven CT Systems 5.2.2 Undriven DT Systems 5.2.3 Asymptotic Stability of LTI Systems 5.3 General Response in Modal Coordinates 5.3.1 Driven CT Systems 5.3.2 Driven DT Systems 5.3.3 Similarity Transformations and Diagonalization 5.4 Transfer Functions, Hidden Modes, Reachability, and Observability 5.4.1 Input-State-Output Structure of CT Systems 5.4.2 Input-State-Output Structure of DT Systems 5.5 Further Reading Problems Basic Problems Advanced Problems Extension Problems 6. State Observers and State Feedback 6.1 Plant and Model 6.2 State Estimation and Observers 6.2.1 Real-Time Simulation 6.2.2 The State Observer 6.2.3 Observer Design 6.3 State Feedback Control 6.3.1 Open-Loop Control 6.3.2 Closed-Loop Control via LTI State Feedback 6.3.3 LTI State Feedback Design 6.4 Observer-Based Feedback Control 6.5 Further Reading Problems <p style="margi

SynopsisFor 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., 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., Key Benefit: 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. KEY TOPICS: 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 Market This book is useful for anyone studying introductory engineering.

LC Classification NumberTK5102.9.O673 2014