LEADER 05607nam 22007814a 450 001 9911019261303321 005 20200520144314.0 010 $a9786610339648 010 $a9781280339646 010 $a1280339640 010 $a9780470024133 010 $a0470024135 010 $a9780470024126 010 $a0470024127 035 $a(CKB)1000000000357192 035 $a(EBL)244866 035 $a(SSID)ssj0000182876 035 $a(PQKBManifestationID)11166908 035 $a(PQKBTitleCode)TC0000182876 035 $a(PQKBWorkID)10172454 035 $a(PQKB)11715200 035 $a(MiAaPQ)EBC244866 035 $a(PPN)170212882 035 $a(OCoLC)171257291 035 $a(FR-PaCSA)41000259 035 $a(CaSebORM)9780470024119 035 $a(OCoLC)842846312 035 $a(OCoLC)ocn842846312 035 $a(FRCYB41000259)41000259 035 $a(Perlego)2762598 035 $a(EXLCZ)991000000000357192 100 $a20050928d2005 uy 0 101 0 $aeng 135 $aur|n|---||||| 181 $ctxt 182 $cc 183 $acr 200 10$aIntroduction to random signals and noise /$fWim C. van Etten 205 $a1st edition 210 $aChichester, England ;$aHoboken, NJ $cWiley$dc2005 215 $a1 online resource (271 p.) 300 $aDescription based upon print version of record. 311 08$a9780470024119 311 08$a0470024119 320 $aIncludes bibliographical references and index. 327 $aIntroduction 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 327 $a2.1.3 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 327 $a3.1 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 327 $a4.2.3 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 327 $a5.2 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 327 $a6.6 Problems 330 $aRandom 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 de 517 3 $aRandom signals and noise 606 $aSignal processing 606 $aStochastic processes 606 $aRandom noise theory 615 0$aSignal processing. 615 0$aStochastic processes. 615 0$aRandom noise theory. 676 $a621.382/2 700 $aEtten$b Wim van$01842076 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9911019261303321 996 $aIntroduction to random signals and noise$94422033 997 $aUNINA