AP9314 STATISTICAL SIGNAL PROCESSING SYLLABUS | ANNA UNIVERSITY ME OC OPTICAL COMMUNICATION 1ST SEM SYLLABUS REGULATION 2009 2011 2012-2013 BELOW IS THE ANNA UNIVERSITY FIRST SEMESTER M.E OPTICAL COMMUNICATION 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
AP9314 STATISTICAL SIGNAL PROCESSING LT 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.
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)
AP9314 STATISTICAL SIGNAL PROCESSING LT 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.
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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