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EC8091 ADVANCED DIGITAL SIGNAL PROCESSING Lecture Notes Download EC8091 ADVANCED DIGITAL SIGNAL PROCESSING Lecture Notes Download
Department  Electronics Communication Engineering
Year 3rd Year
Semester 6th Semester
University Anna University
Regulation  R2017
Subject Code EC8091
Subject Name ADVANCED DIGITAL SIGNAL PROCESSING
Download File EC8091 ADVANCED DIGITAL SIGNAL PROCESSING Lecture Notes, Books, Important 2 Marks Question and Answers, 16 Mark Question with Answers, Syllabus & Question Bank

 

 

EC8091 ADVANCED DIGITAL SIGNAL PROCESSING Syllabus

UNIT I DISCRETE-TIME RANDOM PROCESSES
Random variables – ensemble averages a review, random processes – ensemble averages, autocorrelation and autocovariance matrices, ergodic random process, white noise, filtering random processes, spectral factorization, special types of random processes – AR, MA, ARMA

UNIT II SPECTRUM ESTIMATION
Bias and consistency, Non-parametric methods – Periodogram, modified-Periodogram – performance analysis. Bartlett’s method, Welch’s method, Blackman-Tukey method. Performance comparison. Parametric methods – autoregressive (AR) spectrum estimation – autocorrelation method, Prony’s method, solution using Levinson Durbin recursion.

UNIT III OPTIMUM FILTERS
Wiener filters – FIR Wiener filter – discrete Wiener Hopf equation, Applications – filtering, linear prediction. IIR Wiener filter – causal and non-causal filters. Recursive estimators – discrete Kalman filter.

UNIT IV ADAPTIVE FILTERS
Principles and properties of adaptive filters – FIR adaptive filters. Adaptive algorithms – steepest descent algorithm, the LMS algorithm – convergence. Applications of adaptive filtering – noise cancellation, channel equalization.

UNIT V MULTIRESOLUTION ANALYSIS
Short-time Fourier transform – Heisenberg uncertainty principle. Principles of multi-resolution analysis – sub-band coding, the continuous and discrete wavelet transform – properties. Applications of wavelet transform – noise reduction, image compression.

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