Detection, estimation, and modulation theory . Part III Rasar-sonor signal processing and Gaussian signals in noise / / Harry L. Van Trees

• Record Nr.: UNINA9911019970903321
• Autore: Van Trees Harry L
• Pubbl/distr/stampa: New York, : Wiley, 2001
• ISBN: 9786610541850; 9781280541858; 1280541857; 9780470346655; 0470346655; 9780471463818; 0471463817; 9780471221098; 0471221090; 9781601195579; 1601195575
• Descrizione fisica: 1 online resource (647 p.)
• Disciplina: 621.381536
• Soggetti: Signal theory (Telecommunication); Modulation (Electronics); Estimation theory
• Lingua di pubblicazione: Inglese
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Note generali: Description based upon print version of record.
• Nota di bibliografia: Includes bibliographical references and indexes.
• Nota di contenuto: Contents; 1 Introduction; 1.1 Review of Parts I and II; 1.2 Random Signals in Noise; 1.3 Signal Processing in Radar-Sonar Systems; References; 2 Detection of Gaussian Signals in White Gaussian Noise; 2.1 Optimum Receivers; 2.1.1 Canonical Realization No. 1: Estimator-Correlator; 2.1.2 Canonical Realization No. 2: Filter-Correlator Receiver; 2.1.3 Canonical Realization No. 3: Filter-Squarer-Integrator (FSI) Receiver; 2.1.4 Canonical Realization No. 4: Optimum Realizable Filter Receiver; 2.1.5 Canonical Realization No. 4S: State-variable Realization; 2.1.6 Summary: Receiver Structures; 2.2 Performance2.2.1 Closed-form Expression for μ(s); 2.2.2 ; Approximate Error Expressions; 2.2.3 An Alternative Expression for μ[sub(R)](S); 2.2.4 Performance for a Typical System; 2.3 Summary: Simple Binary Detection; 2.4 Problems; References; 3 General Binary Detection: Gaussian Processes; 3.1 Model and Problem Classification; 3.2 Receiver Structures; 3.2.1 Whitening Approach; 3.2.2 Various Implementations of the Likelihood Ratio Test; 3.2.3 Summary: Receiver Structures; 3.3 Performance; 3.4 Four Special Situations; 3.4.1 Binary Symmetric Case; 3.4.2 Non-zero Means; 3.4.3 Stationary ""Carrier-symmetric"" Bandpass Problems3.4.4 Error Probability for the Binary Symmetric Bandpass Problem; 3.5 General Binary Case: White Noise Not Necessarily Present: Singular Tests; 3.5.1 Receiver Derivation; 3.5.2 Performance: General Binary Case; 3.5.3 Singularity; 3.6 Summary: General Binary Problem; 3.7 Problems; References; 4 Special Categories of Detection Problems; 4.1 Stationary Processes: Long Observation Time; 4.1.1 Simple Binary Problem; 4.1.2 General Binary Problem; 4.1.3 Summary: SPLOT Problem; 4.2 Separable Kernels; 4.2.1 Separable Kernel Model; 4.2.2 Time Diversity4.2.3 Frequency Diversity; 4.2.4 Summary: Separable Kernels; 4.3 Low-Energy-Coherence (LEC) Case; 4.4 Summary; 4.5 Problems; References; 5 Discussion: Detection of Gaussian Signals; 5.1 Related Topics; 5.1.1 M-ary Detection: Gaussian Signals in Noise; 5.1.2 Suboptimum Receivers; 5.1.3 Adaptive Receivers; 5.1.4 Non-Gaussian Processes; 5.1.5 Vector Gaussian Processes; 5.2 Summary of Detection Theory; 5.3 Problems; References; 6 Estimation of the Parameters of a Random Process; 6.1 Parameter Estimation Model; 6.2 Estimator Structure; 6.2.1 Derivation of the Likelihood Function6.2.2 Maximum Likelihood and Maximum A-Posteriori Probability Equations; 6.3 Performance Analysis; 6.3.1 A Lower Bound on the Variance; 6.3.2 Calculation of J[sup(2)](A); 6.3.3 Lower Bound on the Mean-Square Error; 6.3.4 Improved Performance Bounds; 6.4 Summary; 6.5 Problems; References; 7 Special Categories of Estimation Problems; 7.1 Stationary Processes: Long Observation Time; 7.1.1 General Results; 7.1.2 Performance of Truncated Estimates; 7.1.3 Suboptimum Receivers; 7.1.4 Summary; 7.2 Finite-State Processes; 7.3 Separable Kernels; 7.4 Low-Energy-Coherence Case
• Sommario/riassunto: Paperback reprint of one of the most respected classics in the history of engineering publicationTogether with the reprint of Part I and the new Part IV, this will be the most complete treatment of the subject availableProvides a highly-readable discussion of Signal Processing and NoiseFeatures numerous problems and illustrations to help promote understanding of the topicsContents are highly applicable to current systems