EC870 Architectures for Signal Processing and Machine Learning

Course Name: 

EC870 Architectures for Signal Processing and Machine Learning

Programme: 

M.Tech(SPML)

Category: 

Elective (Ele)

Credits (L-T-P): 

(4-0-0) 4

Content: 

Representation of digital signal processing systems: block diagrams, signal flow graphs, data-flow graphs, dependence graphs; pipelining and parallel processing for high-speed and low power realizations; iteration bound, algorithms to compute iteration bound, retiming of data-flow graphs; unfolding transformation of dataflow graphs; systolic architecture design, architectures for real and complex fast Fourier transforms; stochastic logic based computing, computing digital filters, arithmetic functions and machine learning functions using stochastic computing; Neural Network architectures.

References: 

K.K. Parhi, VLSI Digital signal processing systems: Design and implementation, John Wiley, 1999.
Lars Wanhammar, DSP Integrated Circuits, Academic Press, 1999.
Sen M. Kuo Bob H. LeeWenshun Tian, Real‐Time Digital Signal Processing: Implementations and Applications, John Wiley & Sons, Ltd, 2006.
Roger Woods, John McAllister, Gaye Lightbody, Ying Yi, FPGA Based Implementation of Signal Processing Systems, John Wile, 2017.
U. Meyer-Baese, Digital Signal Processing with Field Programmable Gate Arrays, 4th Ed. Springer, 2014.
Recent literature

Department: 

Electronics and Communication Engineering(ECE)
 

Contact us

Dr. T. Laxminidhi,  Professor and Head, 
Department of E&C, NITK, Surathkal
P. O. Srinivasnagar,
Mangalore - 575 025 Karnataka, India.

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