05840nam 2200781 a 450 991082185080332120240313194054.01-118-53970-21-118-53992-3(CKB)2670000000340410(EBL)1166811(OCoLC)850209477(SSID)ssj0000856001(PQKBManifestationID)11488949(PQKBTitleCode)TC0000856001(PQKBWorkID)10807484(PQKB)10435396(OCoLC)843193425(MiAaPQ)EBC1166811(Au-PeEL)EBL1166811(CaPaEBR)ebr10718826(CaONFJC)MIL497765(MiAaPQ)EBC7103786(Au-PeEL)EBL7103786(PPN)188242651(JP-MeL)3000111677(EXLCZ)99267000000034041020150303d2013 uy 0engur|n|---|||||txtccrDetection estimation and modulation theoryPart IDetection, estimation, and filtering theory /Harry L. Van Trees, Kristine L. Bell ; with Zhi Tian2nd ed.Hoboken, N.J. Wileyc20131 online resource (1175 p.)880-03Detection, estimation, and modulation theoryIncludes bibliographical references (p. 1125-1143) and index0-470-54296-9 Includes bibliographical references and index.Detection, Estimation, and Modulation Theory: Part I -Detection, Estimation, and Filtering Theory; Contents; Preface; Preface to the First Edition; 1 Introduction; 1.1 Introduction; 1.2 Topical Outline; 1.3 Possible Approaches; 1.4 Organization; 2 Classical Detection Theory; 2.1 Introduction; 2.2 Simple Binary Hypothesis Tests; 2.2.1 Decision Criteria; 2.2.2 Performance: Receiver Operating Characteristic; 2.3 M Hypotheses; 2.4 Performance Bounds and Approximations; 2.5 Monte Carlo Simulation; 2.5.1 Monte Carlo Simulation Techniques; 2.5.2 Importance Sampling; 2.5.2.1 Simulation of PF2.5.2.2 Simulation of PM2.5.2.3 Independent Observations; 2.5.2.4 Simulation of the ROC; 2.5.2.5 Examples; 2.5.2.6 Iterative Importance Sampling; 2.5.3 Summary; 2.6 Summary; 2.7 Problems; 3 General Gaussian Detection; 3.1 Detection of Gaussian Random Vectors; 3.1.1 Real Gaussian Random Vectors; 3.1.2 Circular Complex Gaussian Random Vectors; 3.1.3 General Gaussian Detection; 3.1.3.1 Real Gaussian Vectors; 3.1.3.2 Circular Complex Gaussian Vectors; 3.1.3.3 Summary; 3.2 Equal Covariance Matrices; 3.2.1 Independent Components with Equal Variance3.2.2 Independent Components with Unequal Variances3.2.3 General Case: Eigendecomposition; 3.2.4 Optimum Signal Design; 3.2.5 Interference Matrix: Estimator-Subtractor; 3.2.6 Low-Rank Models; 3.2.7 Summary; 3.3 Equal Mean Vectors; 3.3.1 Diagonal Covariance Matrix on H0: Equal Variance; 3.3.1.1 Independent, Identically Distributed Signal Components; 3.3.1.2 Independent Signal Components: Unequal Variances; 3.3.1.3 Correlated Signal Components; 3.3.1.4 Low-Rank Signal Model; 3.3.1.5 Symmetric Hypotheses, Uncorrelated Noise; 3.3.2 Nondiagonal Covariance Matrix on H0; 3.3.2.1 Signal on H1 Only3.3.2.2 Signal on Both Hypotheses3.3.3 Summary; 3.4 General Gaussian; 3.4.1 Real Gaussian Model; 3.4.2 Circular Complex Gaussian Model; 3.4.3 Single Quadratic Form; 3.4.4 Summary; 3.5 M Hypotheses; 3.6 Summary; 3.7 Problems; 4 Classical Parameter Estimation; 4.1 Introduction; 4.2 Scalar Parameter Estimation; 4.2.1 Random Parameters: Bayes Estimation; 4.2.2 Nonrandom Parameter Estimation; 4.2.3 Bayesian Bounds; 4.2.3.1 Lower Bound on the MSE; 4.2.3.2 Asymptotic Behavior; 4.2.4 Case Study; 4.2.5 Exponential Family; 4.2.5.1 Nonrandom Parameters; 4.2.5.2 Random Parameters4.2.6 Summary of Scalar Parameter Estimation4.3 Multiple Parameter Estimation; 4.3.1 Estimation Procedures; 4.3.1.1 Random Parameters; 4.3.1.2 Nonrandom Parameters; 4.3.2 Measures of Error; 4.3.2.1 Nonrandom Parameters; 4.3.2.2 Random Parameters; 4.3.3 Bounds on Estimation Error; 4.3.3.1 Nonrandom Parameters; 4.3.3.2 Random Parameters; 4.3.4 Exponential Family; 4.3.4.1 Nonrandom Parameters; 4.3.4.2 Random Parameters; 4.3.5 Nuisance Parameters; 4.3.5.1 Nonrandom Parameters; 4.3.5.2 Random Parameters; 4.3.5.3 Hybrid Parameters; 4.3.6 Hybrid Parameters; 4.3.6.1 Joint ML and MAP Estimation4.3.6.2 Nuisance ParametersOriginally published in 1968, Harry Van Trees's Detection, Estimation, and Modulation Theory, Part I is one of the great time-tested classics in the field of signal processing. Highly readable and practically organized, it is as imperative today for professionals, researchers, and students in optimum signal processing as it was over thirty years ago. The second edition is a thorough revision and expansion almost doubling the size of the first edition and accounting for the new developments thus making it again the most comprehensive and up-to-date treatment of the subject. With a wide rangeNew York Academy of Sciences Signal theory (Telecommunication)Modulation (Electronics)Estimation theorySignal theory (Telecommunication)Modulation (Electronics)Estimation theory.621.382/2547.1njb/09621.381536njb/09Van Trees Harry L2732Bell Kristine L323713Tian Zhi1972-1682669MiAaPQMiAaPQMiAaPQBOOK9910821850803321Detection estimation and modulation theory4052951UNINA