EC870 Architectures for Signal Processing and Machine Learning
Course Name:
EC870 Architectures for Signal Processing and Machine Learning
Programme:
M.Tech (VLSI)
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)