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BL
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| Record Number
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1040907
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| Doc. No
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b795277
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| Main Entry
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Etten, Wim van.
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| Title & Author
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Introduction to random signals and noise /\ Wim C. van Etten.
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| Publication Statement
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Chichester, England ;Hoboken, NJ :: Wiley,, ©2005.
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| Page. NO
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1 online resource (xiii, 255 pages) :: illustrations
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| ISBN
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0470024119
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: 0470024127
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: 0470024135
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: 9780470024119
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: 9780470024126
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: 9780470024133
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| Bibliographies/Indexes
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Includes bibliographical references and index.
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| Contents
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Introduction to Random Signals and Noise; Contents; Preface; 1 Introduction; 1.1 Random Signals and Noise; 1.2 Modelling; 1.3 The Concept of a Stochastic Process; 1.3.1 Continuous Stochastic Processes; 1.3.2 Discrete-Time Processes (Continuous Random Sequences); 1.3.3 Discrete Stochastic Processes; 1.3.4 Discrete Random Sequences; 1.3.5 Deterministic Function versus Stochastic Process; 1.4 Summary; 2 Stochastic Processes; 2.1 Stationary Processes; 2.1.1 Cumulative Distribution Function and Probability Density Function; 2.1.2 First-Order Stationary Processes
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2.1.3 Second-Order Stationary Processes2.1.4 Nth-Order Stationary Processes; 2.2 Correlation Functions; 2.2.1 The Autocorrelation Function, Wide-Sense Stationary Processes and Ergodic Processes; 2.2.2 Cyclo-Stationary Processes; 2.2.3 The Cross-Correlation Function; 2.2.4 Measuring Correlation Functions; 2.2.5 Covariance Functions; 2.2.6 Physical Interpretation of Process Parameters; 2.3 Gaussian Processes; 2.4 Complex Processes; 2.5 Discrete-Time Processes; 2.5.1 Mean, Correlation Functions and Covariance Functions; 2.6 Summary; 2.7 Problems; 3 Spectra of Stochastic Processes
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3.1 The Power Spectrum3.2 The Bandwidth of a Stochastic Process; 3.3 The Cross-Power Spectrum; 3.4 Modulation of Stochastic Processes; 3.4.1 Modulation by a Random Carrier; 3.5 Sampling and Analogue-To-Digital Conversion; 3.5.1 Sampling Theorems; 3.5.2 A/D Conversion; 3.6 Spectrum of Discrete-Time Processes; 3.7 Summary; 3.8 Problems; 4. Linear Filtering of Stochastic Processes; 4.1 Basics of Linear Time-Invariant Filtering; 4.2 Time Domain Description of Filtering of Stochastic Processes; 4.2.1 The Mean Value of the Filter Output; 4.2.2 The Autocorrelations Function of the Output
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4.2.3 Cross-Correlation of the Input and Output4.3 Spectra of the Filter Output; 4.4 Noise Bandwidth; 4.4.1 Band-Limited Processes and Systems; 4.4.2 Equivalent Noise Bandwidth; 4.5 Spectrum of a Random Data Signal; 4.6 Principles of Discrete-Time Signals and Systems; 4.6.1 The Discrete Fourier Transform; 4.6.2 The z-Transform; 4.7 Discrete-Time Filtering of Random Sequences; 4.7.1 Time Domain Description of the Filtering; 4.7.2 Frequency Domain Description of the Filtering; 4.8 Summary; 4.9 Problems; 5 Bandpass Processes; 5.1 Description of Deterministic Bandpass Signals
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5.2 Quadrature Components of Bandpass Processes5.3 Probability Density Functions of the Envelope and Phase of Bandpass Noise; 5.4 Measurement of Spectra; 5.4.1 The Spectrum Analyser; 5.4.2 Measurement of the Quadrature Components; 5.5 Sampling of Bandpass Processes; 5.5.1 Conversion to Baseband; 5.5.2 Direct Sampling; 5.6 Summary; 5.7 Problems; 6 Noise in Networks and Systems; 6.1 White and Coloured Noise; 6.2 Thermal Noise in Resistors; 6.3 Thermal Noise in Passive Networks; 6.4 System Noise; 6.4.1 Noise in Amplifiers; 6.4.2 The Noise Figure; 6.4.3 Noise in Cascaded systems; 6.5 Summary
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| Abstract
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Random signals and noise are present in many engineering systems and networks. Signal processing techniques allow engineers to distinguish between useful signals in audio, video or communication equipment, and interference, which disturbs the desired signal. With a strong mathematical grounding, this text provides a clear introduction to the fundamentals of stochastic processes and their practical applications to random signals and noise. With worked examples, problems, and detailed appendices, Introduction to Random Signals and Noise gives the reader the knowledge to design optimum systems for effectively coping with unwanted signals. Key features: Considers a wide range of signals and noise, including analogue, discrete-time and bandpass signals in both time and frequency domains. Analyses the basics of digital signal detection using matched filtering, signal space representation and correlation receiver. Examines optimal filtering methods and their consequences. Presents a detailed discussion of the topic of Poisson processes and shot noise. An excellent resource for professional engineers developing communication systems, semiconductor devices, and audio and video equipment, this book is also ideal for senior undergraduate and graduate students in Electronic and Electrical Engineering.
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| Subject
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Random noise theory.
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Signal processing.
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Stochastic processes.
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COMPUTERS-- Information Theory.
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Random noise theory.
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Signal processing.
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Stochastic processes.
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TECHNOLOGY ENGINEERING-- Signals Signal Processing.
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| Dewey Classification
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621.382/2
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| LC Classification
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TK5102.9.E78 2005eb
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| NLM classification
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53.18bcl
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