AP4151 Advanced Digital Signal Processing Syllabus:
AP4151 Advanced Digital Signal Processing Syllabus – Anna University PG Syllabus Regulation 2021
COURSE OBJECTIVES:
To describe fundamental concepts of DSP and Discrete Transforms
To design digital filters design
To estimate power spectrum using non- parametric and parametric methods
To analyze the Multirate Signal processing by decimation and interpolation.
To apply the concept of multirate signal processing for various applications
UNIT I DIGITAL SIGNAL PROCESSING
Sampling of analog signals – Selection of sampling frequency – Frequency response – Transfer functions – Filter structures – Fast Fourier Transform (FFT) Algorithms – Image coding – DCT.
UNIT II DIGITAL FILTER DESIGN
IIR and FIR Filters: Filter structures, Implementation of Digital Filters – 2nd Order Narrow Band Filter and 1st Order All Pass Filter, Frequency sampling structures of FIR, Lattice structures, Forward and Backward prediction error filters, Reflection coefficients for lattice realization, Implementation of lattice structures for IIR filters, Advantages of lattice structures.
UNIT III ESTIMATION OF POWER SPECTRUM
Non-Parametric Methods: Estimation of spectra from finite duration observation of signals,: Bartlett, Welch & Blackman-Tukey methods, Performance Comparison. Parametric Methods: Autocorrelation & Its Properties, Relation between auto correlation & model parameters, AR Models – Yule-Walker & Burg Methods, MA & ARMA models for power spectrum estimation.
UNIT IV MULTI RATE SIGNAL PROCESSING
Decimation by a factor D – Interpolation by a factor I – Sampling rate conversion by a rational factor I/D, Multistage Implementation of Sampling Rate Conversion, Filter design and Implementation for sampling rate conversion. Up-sampling using All Pass Filter.
UNIT V APPLICATIONS OF MULTI RATE SIGNAL PROCESSING AND DSP INTEGRATED CIRCUITS
Design of Phase Shifters, Interfacing of Digital Systems with Different Sampling Rates, Implementation of Narrow Band Low Pass Filters, Implementation of Digital Filter Banks, Subband Coding of Speech Signals, Quadrature Mirror Filters, Over Sampling A/D and D/A Conversion.
TOTAL: 45 PERIODS
COURSE OUTCOMES:
Upon completion of the course, the students will be able to
CO1: Describe the basics of Digital Signal Processing and Discrete Time Transforms.
CO2. Design and implement FIR/IIR digital filters using various structures
CO3. Estimate power spectrum using appropriate parametric/non-parametric method.
CO4: Analyze discrete time system at different sampling frequencies using the concept of Multirate signal processing
CO5: Design discrete time system for the given application using Multi rate signal processing
REFERENCES:
1. J.G.Proakis & D. G.Manolakis Digital Signal Processing: Principles, Algorithms & Applications -, 4th Ed., Pearson Education, 2013.
2. Alan V Oppenheim & Ronald W Schaffer Discrete Time signal processing, Pearson Education, 2014.
3. Keshab K. Parhi, ‘VLSI Digital Signal Processing Systems Design and Implementation”, John Wiley& Sons, 2007.
4. Steven. M .Kay, Modern Spectral Estimation: Theory & Application –PHI, 2009.
5. P.P.Vaidyanathan, Multi Rate Systems and Filter Banks , Pearson Education, 1993.
6. Emmanuel C. Ifeachor, Barrie W. Jervis, “Digital Signal Processing–A practical approach”, Second Edition, Harlow, Prentice Hall, 2011.