Tabla de Contenidos: “…-- Preface xv -- 1 Introduction 1 -- 1.1 Vision: “Big Data” 1 -- 1.2 Cognitive Radio: System Concepts 2 -- 1.3 Spectrum Sensing Interface and Data Structures 2 -- 1.4 Mathematical Machinery 4 -- 1.4.1 Convex Optimization 4 -- 1.4.2 Game Theory 6 -- 1.4.3 “Big Data” Modeled as Large Random Matrices 6 -- 1.5 Sample Covariance Matrix 10 -- 1.6 Large Sample Covariance Matrices of Spiked Population Models 11 -- 1.7 Random Matrices and Noncommutative Random Variables 12 -- 1.8 Principal Component Analysis 13 -- 1.9 Generalized Likelihood Ratio Test (GLRT) 13 -- 1.10 Bregman Divergence for Matrix Nearness 13 -- 2 Spectrum Sensing: Basic Techniques 15 -- 2.1 Challenges 15 -- 2.2 Energy Detection: No Prior Information about Deterministic or Stochastic Signal 15 -- 2.2.1 Detection in White Noise: Lowpass Case 16 -- 2.2.2 Time-Domain Representation of the Decision Statistic 19 -- 2.2.3 Spectral Representation of the Decision Statistic 19 -- 2.2.4 Detection and False Alarm Probabilities over AWGN Channels 20 -- 2.2.5 Expansion of Random Process in Orthonormal Series with Uncorrelated Coefficients: The Karhunen-Loeve Expansion 21 -- 2.3 Spectrum Sensing Exploiting Second-Order Statistics 23 -- 2.3.1 Signal Detection Formulation 23 -- 2.3.2 Wide-Sense Stationary Stochastic Process: Continuous-Time 24 -- 2.3.3 Nonstationary Stochastic Process: Continuous-Time 25 -- 2.3.4 Spectrum Correlation-Based Spectrum Sensing for WSS Stochastic Signal: Heuristic Approach 29 -- 2.3.5 Likelihood Ratio Test of Discrete-Time WSS Stochastic Signal 32 -- 2.3.6 Asymptotic Equivalence between Spectrum Correlation and Likelihood Ratio Test 35 -- 2.3.7 Likelihood Ratio Test of Continuous-Time Stochastic Signals in Noise: Selin's Approach 36 -- 2.4 Statistical Pattern Recognition: Exploiting Prior Information about Signal through Machine Learning 39 -- 2.4.1 Karhunen-Loeve Decomposition for Continuous-Time Stochastic Signal 39 -- 2.5 Feature Template Matching 42 -- 2.6 Cyclostationary Detection 47 -- 3 Classical Detection 51.…”

“…The book looks at key terms-Intimate Reckoning, Intimate Revolution, Resistance Negotiation, and Revolutionary Black Grace-that enable people to challenge white supremacy. Intimate Reckoning shows white women how they can examine their role in sustaining white supremacy, while Intimate Revolution teaches Black women to unlearn the language of whiteness that teaches them their sole value is labor. …”