AP9211 ADVANCED DIGITAL SIGNAL PROCESSING SYLLABUS | ANNA UNIVERSITY ME APPLIED ELECTRONICS 1ST SEM SYLLABUS REGULATION 2009 2011 2012-2013 BELOW IS THE ANNA UNIVERSITY FIRST SEMESTER M.E APPLIED ELECTRONICS DEPARTMENT SYLLABUS, TEXTBOOKS, REFERENCE BOOKS,EXAM PORTIONS,QUESTION BANK,PREVIOUS YEAR QUESTION PAPERS,MODEL QUESTION PAPERS, CLASS NOTES, IMPORTANT 2 MARKS, 8 MARKS, 16 MARKS TOPICS. IT IS APPLICABLE FOR ALL STUDENTS ADMITTED IN THE YEAR 2011 2012-2013 (ANNA UNIVERSITY CHENNAI,TRICHY,MADURAI, TIRUNELVELI,COIMBATORE), 2009 REGULATION OF ANNA UNIVERSITY CHENNAI AND STUDENTS ADMITTED IN ANNA UNIVERSITY CHENNAI DURING 2009
AP9211 ADVANCED DIGITAL SIGNAL PROCESSING L T P C
3 0 0 3
UNIT I DISCRETE RANDOM SIGNAL PROCESSING 9
Discrete Random Processes- Ensemble Averages, Stationary processes, Bias and
Estimation, Autocovariance, Autocorrelation, Parseval’s theorem, Wiener-Khintchine
relation, White noise, Power Spectral Density, Spectral factorization, Filtering Random
Processes, Special types of Random Processes – ARMA, AR, MA – Yule-Walker
equations.
3
UNIT II SPECTRAL ESTIMATION 9
Estimation of spectra from finite duration signals, Nonparametric methods -
Periodogram, Modified periodogram, Bartlett, Welch and Blackman-Tukey methods,
Parametric methods – ARMA, AR and MA model based spectral estimation, Solution
using Levinson-Durbin algorithm
UNIT III LINEAR ESTIMATION AND PREDICTION 9
Linear prediction – Forward and Backward prediction, Solution of Prony’s normal
equations, Least mean-squared error criterion, Wiener filter for filtering and prediction,
FIR and IIR Wiener filters, Discrete Kalman filter
UNIT IV ADAPTIVE FILTERS 9
FIR adaptive filters – adaptive filter based on steepest descent method- Widrow-Hopf
LMS algorithm, Normalized LMS algorithm, Adaptive channel equalization, Adaptive
echo cancellation, Adaptive noise cancellation, RLS adaptive algorithm.
UNIT V MULTIRATE DIGITAL SIGNAL PROCESSING 9
Mathematical description of change of sampling rate – Interpolation and Decimation,
Decimation by an integer factor, Interpolation by an integer factor, Sampling rate
conversion by a rational factor, Polyphase filter structures, Multistage implementation of
multirate system, Application to subband coding – Wavelet transform
TOTAL: 45 PERIODS
REFERENCES:
1. Monson H. Hayes, ‘Statistical Digital Signal Processing and Modeling”, John Wiley
and Sons, Inc, Singapore, 2002
2. John J. Proakis, Dimitris G. Manolakis, : Digital Signal Processing’, Pearson
Education, 2002
3. Rafael C. Gonzalez, Richard E. Woods, “ Digital Image Processing”, Pearson
Education Inc.,Second Edition, 2004 (For Wavelet Transform Topic)
AP9211 ADVANCED DIGITAL SIGNAL PROCESSING L T P C
3 0 0 3
UNIT I DISCRETE RANDOM SIGNAL PROCESSING 9
Discrete Random Processes- Ensemble Averages, Stationary processes, Bias and
Estimation, Autocovariance, Autocorrelation, Parseval’s theorem, Wiener-Khintchine
relation, White noise, Power Spectral Density, Spectral factorization, Filtering Random
Processes, Special types of Random Processes – ARMA, AR, MA – Yule-Walker
equations.
3
UNIT II SPECTRAL ESTIMATION 9
Estimation of spectra from finite duration signals, Nonparametric methods -
Periodogram, Modified periodogram, Bartlett, Welch and Blackman-Tukey methods,
Parametric methods – ARMA, AR and MA model based spectral estimation, Solution
using Levinson-Durbin algorithm
UNIT III LINEAR ESTIMATION AND PREDICTION 9
Linear prediction – Forward and Backward prediction, Solution of Prony’s normal
equations, Least mean-squared error criterion, Wiener filter for filtering and prediction,
FIR and IIR Wiener filters, Discrete Kalman filter
UNIT IV ADAPTIVE FILTERS 9
FIR adaptive filters – adaptive filter based on steepest descent method- Widrow-Hopf
LMS algorithm, Normalized LMS algorithm, Adaptive channel equalization, Adaptive
echo cancellation, Adaptive noise cancellation, RLS adaptive algorithm.
UNIT V MULTIRATE DIGITAL SIGNAL PROCESSING 9
Mathematical description of change of sampling rate – Interpolation and Decimation,
Decimation by an integer factor, Interpolation by an integer factor, Sampling rate
conversion by a rational factor, Polyphase filter structures, Multistage implementation of
multirate system, Application to subband coding – Wavelet transform
TOTAL: 45 PERIODS
REFERENCES:
1. Monson H. Hayes, ‘Statistical Digital Signal Processing and Modeling”, John Wiley
and Sons, Inc, Singapore, 2002
2. John J. Proakis, Dimitris G. Manolakis, : Digital Signal Processing’, Pearson
Education, 2002
3. Rafael C. Gonzalez, Richard E. Woods, “ Digital Image Processing”, Pearson
Education Inc.,Second Edition, 2004 (For Wavelet Transform Topic)
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