Course | Postgraduate |
Semester | Sem. I |
Subject Code | AVD611 |
Subject Title | Modern Signal Processing |
Analysis of LTI system: Phase and Magnitude response of the system, Minimum phase, maximum phase, Allpass. Multirate Signal Processing: Interpolation, Decimation, sampling rate conversion, Filter bank design, Polyphase structures. Time-frequency representation; frequency scale and resolution; uncertainty principle, short-time Fourier transform. Multi-resolution concept and analysis, Wavelet transform (CWT, DWT). Optimum Linear Filters: Innovations Representation of a Stationary Random Process, Forward and Backward linear prediction, Solution of the Normal Equations. Power Spectral Estimation: Estimation of Spectra from Finite Duration Observations of a signal, the Periodogram, Bartlett, Welch and Blackman, Tukey methods, Comparison of performance of Non-Parametric Power Spectrum Estimation Methods. Parametric Methods: Auto-Correlation and Model Parameters, AR (Auto-Regressive), Moving Average (MA), and ARMA Spectrum Estimation. Frequency Estimation-Eigen Decomposition of autocorrelation matrix, Piscaranko’s Harmonic Decomposition Methods, MUSIC Method. Adaptive Filter Theory: LMS, NLMS and RLS, Linear Prediction. DSP Processor architecture- DSP Number representation for signals, Study of FIxed point and floating-point DSP processor and its architectures.
Same as Reference
1. Mitra, S. K., (2008), Digital Signal Processing, 3 rd Edition, McGraw Hill
2. Oppenheim, Alan V - Discrete-time signal processing, Pearson Education India.
3. Multirate Systems And Filter Banks, P.P. Vaidyanathan, Prentice-Hall, 1993.
4. Statistical digital signal processing and modeling, Monson H.Hayes, Jhon Wiley & Sons.
5.Y. T. Chan, (1993), Wavelet Basics, Kluwer Publishers, Boston.
6.Gerald Kaiser, (1992), A Friendly Guide to Wavelets, Birkhauser, New York
7. Proakis, John G. - Digital signal processing: principles algorithms and applications, PHI.
8. Haykin, Simon S. - Adaptive filter theory, Pearson Education India