Syllabus
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.
Text Books
Same as Reference
References
1. Digital Signal Processing, Mitra, S. K., 3 rd Edition, McGraw Hill 2008.
2. Discrete-time signal processing, Oppenheim, Alan V - 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. Wavelet Basics, Y. T. Chan, Kluwer Publishers, Boston, 1993.
6. A Friendly Guide to Wavelets, Gerald Kaiser, Birkhauser, New York, 1992.
7. Digital signal processing: principles algorithms and applications, Proakis, John G. - PHI.
8. Adaptive filter theory, Haykin, Simon S, Pearson Education India.
Pre-requisites:
1. Undergraduate Signals and Systems
2. Undergraduate Digital Signal Processing
Course Outcomes (COs):
CO1: Ability to design and analyze LTI systems.
CO2: Understand and apply multi rate signal processing in DSP.
CO3: Designing optimum filters and spectral estimators for different signal processing applications
CO4: Apply adaptive signal processing algorithms for real time applications.