K
Keshab K. Parhi
Researcher at University of Minnesota
Publications - 768
Citations - 21763
Keshab K. Parhi is an academic researcher from University of Minnesota. The author has contributed to research in topics: Decoding methods & Adaptive filter. The author has an hindex of 68, co-authored 749 publications receiving 20097 citations. Previous affiliations of Keshab K. Parhi include University of California, Berkeley & University of Warwick.
Papers
More filters
Proceedings ArticleDOI
Complexity reduction of the decoders for interleaved trellis coded modulation schemes for 10 gigabit Ethernet over copper
Yongru Gu,Keshab K. Parhi +1 more
TL;DR: This paper considers the problem of complexity reduction of the decoders for the two interleaved modulation schemes and proposes two complexity reduction schemes.
Proceedings ArticleDOI
Low Cost Parallel Adaptive Filter Structures
Chao Cheng,Keshab K. Parhi +1 more
TL;DR: Two parallel LMS adaptive filtering algorithms with low hardware don't alter the input-output behavior and saves large amount of hardware cost of previous designs, especially when the parallelism level is high.
Journal Article
An efficient pipelined FFT architecture.
Yun-Nan Chang,Keshab K. Parhi +1 more
TL;DR: An efficient VLSI architecture of the pipeline fast Fourier transform (FFT) processor based on radix-4 decimation-in-time algorithm with the use of digit-serial arithmetic units is presented in this article.
Proceedings ArticleDOI
Parallel processing architectures for rank order and stack filters
L.E. Lucke,Keshab K. Parhi +1 more
TL;DR: The authors introduce a systematic method for applying block processing to the rank order and stack filters that takes advantage of shared comparisons within the block structure to generate a block filter with shared substructures whose complexity is reduced.
Journal ArticleDOI
DNA Memristors and Their Application to Reservoir Computing.
Xingyi Liu,Keshab K. Parhi +1 more
TL;DR: In this article , the state of the memristor can be computed from the concentrations of the two output molecules using bipolar fractional coding, and the readout layer effectively maps the projected features to the target output.