Non-Gaussian Statistical Communication Theory (IEEE Series on Digital & Mobile Communication)

Foreword xv Visualizing the Invisible xvii Acknowledgments xxi About the Author xxiii Editor's Note xxv Introduction 1 1 Reception as a Statistical Decision Problem 15 1.1 Signal Detection and Estimation, 15 1.2 Signal Detection and Estimation, 17 1.3 The Reception Situation in General Terms, 22 1.4 System Evaluation, 27 1.5 A Summary of Basic Definitions and Principal Theorems, 35 1.6 Preliminaries: Binary Bayes Detection, 40 1.7 Optimum Detection: On-Off Optimum Processing Algorithms, 46 1.8 Special On-Off Optimum Binary Systems, 50 1.9 Optimum Detection: On-Off Performance Measures and System Comparisons, 57 1.10 Binary Two-Signal Detection: Disjoint and Overlapping Hypothesis Classes, 69 2 Space-Time Covariances and Wave Number Frequency Spectra: I. Noise and Signals with Continuous and Discrete Sampling 77 2.1 Inhomogeneous and Nonstationary Signal and Noise Fields I: Waveforms, Beam Theory, Covariances, and Intensity Spectra, 78 2.2 Continuous Space-Time Wiener-Khintchine Relations, 91 2.3 The W-Kh Relations for Discrete Samples in the Non-Hom-Stat Situation, 102 2.4 The Wiener-Khintchine Relations for Discretely Sampled Random Fields, 108 2.5 Aperture and Arrays-I: An Introduction, 115 2.6 Concluding Remarks, 138 3 Optimum Detection, Space-Time Matched Filters, and Beam Forming in Gaussian Noise Fields 141 3.1 Optimum Detection I: Selected Gaussian Prototypes-Coherent Reception, 142 3.2 Optimum Detection II: Selected Gaussian Prototypes-Incoherent Reception, 154 3.3 Optimal Detection III: Slowly Fluctuating Noise Backgrounds, 176 3.4 Bayes Matched Filters and Their Associated Bilinear and Quadratic Forms, I, 188 3.5 Bayes Matched Filters in the Wave Number-Frequency Domain, 219 3.6 Concluding Remarks, 235 4 Multiple Alternative Detection 239 4.1 Multiple-Alternative Detection: The Disjoint Cases, 239 4.2 Overlapping Hypothesis Classes, 254 4.3 Detection with Decisions Rejection: Nonoverlapping Signal Classes, 262 5 Bayes Extraction Systems: Signal Estimation and Analysis, p(H1) = 1 271 5.1 Decision Theory Formulation, 272 5.2 Coherent Estimation of Amplitude (Deterministic Signals and Normal Noise, p(H1) = 1), 287 5.3 Incoherent Estimation of Signal Amplitude (Deterministic Signals and Normal Noise, p(H1) = 1), 294 5.4 Waveform Estimation (Random Fields), 300 5.5 Summary Remarks, 304 6 Joint Detection and Estimation, p(H1)