Transcription of AnIntroductionto StatisticalSignalProcessing
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AnIntroductionto StatisticalSignalProcessing
IAn Introduction toStatistical Signal ProcessingPr(f F) =P({ : F}) =P(f 1(F))f 1(F)fF-January 4, 2011iiAn Introduction toStatistical Signal ProcessingRobert M. GrayandLee D. DavissonInformation Systems LaboratoryDepartment of Electrical EngineeringStanford UniversityandDepartment of Electrical Engineering and Computer ScienceUniversity of Marylandc 2004 by Cambridge University Press. Copies of the pdf file maybedownloaded for individual use, but multiple copies cannot be made or printedwithout our FamiliesContentsPrefacepageixAcknowledge mentsxiiGlossaryxiii1 Introduction12 Spinning pointers and flipping Probability Discrete probability Continuous probability Elementary conditional Problems733 random variables, vectors, and random Distributions of random random vectors and random Distributions of random Independent random Conditional Statistical detection and Additive Binary detection in Gaussian Statistical Characteristic Gaussian random Simple random Directly given random Discrete time Markov Nonelementary conditional Problems1684 Expectation and Functions of random Functions of several random Properties of Conditional Jointly Gaussian Expectation as Implications for linear Correlation and linear
6.6 Moving-average and autoregressive processes 378 6.7 The discrete time Gauss–Markov process 380 6.8 Gaussian random processes 381 6.9 The Poisson counting process 382 6.10 Compound processes 385 6.11 Composite random processes 386 6.12 ⋆Exponential modulation 387 6.13 ⋆Thermal noise 392 6.14 Ergodicity 395 6.15 Random fields 398 6.16 ...
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