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14EC3001 SDSP Credits 3:0:0
Sugumar D
AP/ECE
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Course Objective
To learn the concepts of signal processing and analyze the statistical properties of signals.
To estimate the spectrum using Parametric and Non Parametric methods.
To design filter / Linear Predictor for Communication Systems.
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Course Outcome
Generate the various special types of random processes in communication receivers.
Estimate / Evaluate the Power Spectrum.
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Course Contents
Discrete Random Processes- Energy- Power Spectral Density - Parsevals Theorem Wiener Khintchine Relation-Periodogram-Sum Decomposition Theorem-Discrete Random Signal Processing using linear system-Parametric and Non-Parametric Spectrum Estimation Methods -Wiener, Kalman Filtering, Levinson-Durban Algorithms Least Square Method, Adaptive Filtering, Non-stationary Signal Analysis, Wigner-Ville Distribution, Multirate Signal Processing- Single and multistage realization - Poly phase realization-Wavelet Analysis
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Text Books
6. S. Haykin, Adaptive filter theory, Prentice Hall, 2005
7. B. Widrow and S.D. Stearns, Adaptive signal processing, Prentice Hall, 1984
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1. Monson H.Hayes, Statistical Digital Signal Processing and Modeling, John Wiley and Sons Inc., New York, Reprint, 2008.
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2.John G.Proakis, DimitrisG.Manolakis, Digital Signal Processing, Prentice Hall of India, 4th Edition,2007.
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3. P.P Vaithyanathan, Multirate systems and filter Banks, Prentice Hall of India, 1993.
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4. Emmanuel C. Ifeacher and Barrie W. Jervis, Digital Signal Processing A Practical Approach, Wesley Longman Ltd., 2nd Edition, 2004
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5. Petre Stoica and Randolph Moses, ``Spectral Analysis of Signals``, Prentice Hall, 2005.
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E-books My collection @
Google drive
E-Books For SDSP & solution
For Matlab
For Labview
For Scilab
Videos NPTL
Youtube
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Office
Follow me in LMS
Room No 206 (2nd Floor of ECE)
E-Mail: [email protected]
