Engineering at Illinois

Chandra Radhakrishnan

A publish.illinois.edu site

Research

Research Interests

My current research interests are in exploiting signal processing, information theoretic, and communication techniques to design robust algorithms and energy efficient systems. Specifically I am interested in:

  • Statistical/Adaptive Signal Processing techniques in circuit design
  • Design of robust algorithms and architectures for nanoscale integrated circuits
  • Signal processing and learning algorithms implementation in in-memory architecture
  • Alternate number systems based circuits and computations
  • Bio-inspired algorithms in signal processing

M.S. Thesis Supervision

Student Name Year Graduation Thesis Title Placement
Aarti Shah May 2017 Successive-Approximation-Register Quantizer based Fifth-Order Delta-Sigma Modulator Texas Instruments
Mei Ling Yeoh August 2018 Analysis of R-2R Digital to Analog Converter with equal current switching Marvel Semiconductor

*Expected

 Undergraduate Research

Student Name Year Graduated Thesis Title
Pei Han Ng May 2016 4-Bit VCO Based Analog-to Digital Converter
Meghana Yadavalli May 2017 A study of Learning Algorithms in Digital Adaptive Filtering

Publications

  1. C.Radhakrishnan and S. Gonugondla, ‘ Adaptive Filtering in Deep In-memory Architectures’, Fifty Third Asilomar Conference on Signals, Systems, Computers, 2019
  2. M. Hussain, W. K . Jenkins, C. Radhakrishnan. ‘The Effects of Arithmetic Roundoff Error on the Lévy Fire Fly Algorithm When Used in Coupled Form Adaptive Filter Structures’, Fifty Third Asilomar Conference on Signals, Systems, Computers, 2019
  3. M. Hussain, W. K . Jenkins, C. Radhakrishnan, ‘Performance Evaluations of Bio-Inspired Adaptive Algorithms Applied to IIR Digital Filters Designed with Coupled Form Second Order Sections’, IEEE Midwest Symposium on Circuits and Systems, 2019
  4. W. K. Jenkins, M. A. Soderstrand, C. Radhakrishnan, ‘Historical Patterns of Emerging Residue Number System Technologies During the Evolution of Computer Engineering and Digital Signal Processing’, International Symposium on Circuits and Systems, 2018
  5. C. Radhakrishnan and A. C. Singer, ‘Conjugate Gradients based Stochastic Adaptive Filters,’ Proc. Fiftieth Asilomar Conference on Signals and Systems, pp. 1569-72, 2017.
  6. C. Radhakrishnan and B. Sahoo, ‘VCO based Nyquist Rate ADC with Fvco of Fs/2,’ IEEE Midwest Symposium on Circuits and Systems, pp. 1021-1024, 2017.
  7. C.Radhakrishnan and A. C. Singer, ‘Recursive Least Square Filtering under stochastic computational errors,’ Proc. Forty Sixth Asilomar Conference on Signals and Systems, pp. 1529-32, 2013.
  8. C.Radhakrishnan and A. C. Singer, ‘Stochastic adaptive filtering using model combinations,’ Proc. Forty Sixth Asilomar Conference on Signals and Systems, pp. 1792-96, 2012.
  9. C.Radhakrishnan and W. K. Jenkins, ‘Reliable Transform Domain Adaptive Filters Designed with a Hybrid Combination of Hardware Modules and Algorithmic Error Detection and Correction,’ IEEE Midwest Symposium on Circuits and Systems, pp. 1-4, 2011.
  10. C.Radhakrishnan and W. K. Jenkins, ‘The 2-D Modulated Discrete Fourier Transform for 2-D Convolution Fast Convolution and Digital Filtering,’ IEEE International Symposium on Circuits and Systems, pp. 1508-1511, 2011.
  11. C.Radhakrishnan and W. K. Jenkins, ‘Fault Tolerant Adaptive Filters Based on Modified Discrete Fourier Transform Architectures,’ IEEE International Symposium on Circuits and Systems, pp. 1271-1274, 2011.
  12. C. Radhakrishnan and W. K. Jenkins, ‘Fault Tolerance in Transform Domain Adaptive Filters Operating with Real-Valued Signals,’ IEEE Trans. Circuits and Systems, vol. 57, No.1, pp. 166-178, Jan 2010.
  13. C. Radhakrishnan, W. K. Jenkins, C. Hunter and R. M. Nickel, ‘Transforms for Reliable and Efficient De-noising of Speech Signals,’ Proc. Forty Fourth Asilomar Conference on Signals and Systems, , pp. 546 – 550, 2010.
  14. C. Radhakrishnan and W. K. Jenkins, ‘Fault Tolerant Filters Based on Modular Arithmetic Coding,’ IEEE Midwest Symposium on Circuits and Systems, pp. 1226-1229, 2010.
  15. C. Hunter, W. K. Jenkins, R.M. Nickel and C. Radhakrishnan, ‘An inventory size feasibility study for fast algorithm analysis/re-synthesis based speech enhancement,’ Electrical Engg. Research Experience for Undergraduates, Department of Electrical Engg, Penn State University(Journal/In House Publication), p. 65, vol. VIII (2010), ISBN 0-913260-10-X.
  16. C. Radhakrishnan and W. K. Jenkins, ‘Modified Discrete Fourier Transforms for Fast Convolution and Adaptive Filtering,’ IEEE International Symposium on Circuits and Systems, pp. 1611-1614, 2010.
  17. C. Radhakrishnan and W. K. Jenkins, ‘Quadratic Modified Fermat Transforms for Fast Convolution and Adaptive Filtering,’ IEEE International Conference on Acoustics, Speech and Signal Processing, pp. 3806-3809, 2010.
  18. W. K. Jenkins, C. Radhakrishnan, and D. F. Marshall, Transform Domain Adaptive Filters, Digital Signal Processing Handbook, CRC Press, 2009.
  19. C. Radhakrishnan and W. K. Jenkins, ‘Fault Tolerant Fermat Number Transform Domain Adaptive Filters Based on Modulus Replication RNS Architectures,’ Proc. Forty Third Asilomar Conference on Signals and Systems, 2009.
  20. C. Radhakrishnan and W. K. Jenkins, ‘Hybrid WHT-MRRNS architectures for fault tolerant adaptive filters,’ IEEE Midwest Symposium on Circuits and Systems, pp. 628 – 631, 2009.
  21. C. Radhakrishnan and W. K. Jenkins, ‘Hybrid WHT-RNS architectures for fault tolerant adaptive filters,’ IEEE International Symposium on Circuits and Systems, pp. 2569 – 2572, 2009.
  22. C. Radhakrishnan and W. K. Jenkins, ‘Fault tolerant adaptive filters based on number theoretic transforms,’ Proc. Forty Second Asilomar Conference on Signals and Systems, pp. 261 – 265, 2008.
  23. C. Radhakrishnan and W. K. Jenkins, ‘Fault tolerant adaptive filters based on the Walsh-Hadamard transform,’ IEEE Midwest Symposium on Circuits and Systems, pp. 153 – 156, 2008.
  24. C. Radhakrishnan and W. K. Jenkins, ‘Special Fault Tolerant properties of FFT-based transform domain Adaptive Filters,’ IEEE International Symposium on Circuits and Systems, 1140 – 1143, 2008.
  25. C. Radhakrishnan, W. K. Jenkins and D. J. Krusienski, ‘Low Power Adaptive Filter based on Combination of Genetic Optimization and Residue Number System Coding’,  Proc. Forty First Asilomar Conference on Signals and Systems, pp. 1417-1421, 2007.
  26. C. Radhakrishnan, W. K. Jenkins and D. J. Krusienski, ‘Adaptive Filters Realized with Nano Scale VLSI Circuit Technology,’  IEEE Midwest Symposium on Circuits and Systems, pp. 413 – 416, 2007.
  27. W. K. Jenkins, C. Radhakrishnan and S. Pal, ‘Fault Tolerant Signal Processing for Masking Transient Errors in VLSI Signal Processors,’ IEEE International Symposium on Circuits and Systems, pp. 2570-2573, 2007.
  28. W. K. Jenkins, C. Radhakrishnan, S. Pal and J. Sabarad, “Fault Tolerant Signal Processing for Nano-scale VLSI Circuit Technology,” Proc. Fortieth Asilomar Conference on Signals and Systems, pp. 926 – 930, 2006.
  29. C. Radhakrishnan and W. K. Jenkins, ‘Conjugate Gradient Algorithm for Series Cascade Nonlinear Adaptive Filters,’ IEEE Midwest Symposium on Circuits and Systems, pp. 33-36, 2004.
  30.  V. Hegde, C. Radhakrishan, D. J. Krusienski and W. K. Jenkins, ‘Architectures and Algorithms for Nonlinear Adaptive Filters,’ Proc. Thirty Sixth Asilomar Conference on Signals and Systems, pp. 1015 -1018, 2002.
  31. V. Hegde, C. Radhakrishan, D. J. Krusienski and W. K. Jenkins, ‘Series-Cascade Nonlinear Adaptive Filters,’ IEEE Midwest Symposium on Circuits and Systems, pp.219-222, 2002.
  32. C.Radhakrishnan, S. Kestur and W. K. Jenkins, ‘Modified Transforms for Fast and Reliable Correlation, Convolution and Digital Filtering,’ Not published