CS-570

Statistical Signal Processing

Postgraduate

This course focuses on problems, algorithms, and solutions for processing signals in a manner that is responsive to a changing environment. Adaptive signal processing systems are developed which take advantage of the statistical properties of the received signals. The course analyzes the performance of adaptive filters and considers the application of the theory to a variety of practical problems such as interference and echo cancellation, signal and system identification, and channel equalization. The class is designed as an advanced statistical signal processing course in which students will build a strong foundation in approaching problems in such diverse areas as acoustic, sonar, radar, geophysical, biomedical, and communications signal processing. Understanding of the theoretical foundations of statistical and adaptive signal processing theory will be achieved through a combination of theoretical and computer-based homework assignments. Course Outline: PART I: BACKGROUND MATERIAL AND LINEAR OPTIMUM FILTERING Topic 1: Background MaterialAdaptive filtering: Concepts and applicationsDiscrete-time signal processingStationary processes and modelsSpectrum analysisLinear algebra: Eigenanalysis and matrix decompositions Topic 2: Wiener FilteringMinimum mean square error (MMSE) and the orthogonality principleDigital Wiener filter and Wiener-Hopf equationsConstrained linear MMSE estimationApplications: Minimum variance beamforming Topic 3: Linear PredictionForward and backward predictionLevinson-Durbin algorithmLattice filtersApplications: DPCM speech coding PART II: ADAPTIVE FILTERING METHODS Topic 4: Stochastic MethodsSteepest Descent algorithmLeast-Mean-Square (LMS) algorithmProperties of the LMSNormalized and frequency-domain LMSGradient adaptive lattice methodsRecursive LMS (RLMS) for adaptive IIR filteringApplications: Active noise control and echo-cancellation Topic 5: Least Squares MethodsLeast squares and orthogonalityRecursive least squares adaptive algorithmsProperties of RLSApplications: ADPCM speech encoding

6

CS-370, CS- 217

http://www.csd.uoc.gr/~hy570