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Venkatesh Elango
University of California, San Diego
2Publications
1H-index
4Citations
Publications 2
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#1Venkatesh Elango (UCSD: University of California, San Diego)H-Index: 1
#2Aashish N Patel (UCSD: University of California, San Diego)H-Index: 1
Last.Vikash Gilja (UCSD: University of California, San Diego)H-Index: 24
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A fundamental challenge in designing brain-computer interfaces (BCIs) is decoding behavior from time-varying neural oscillations. In typical applications, decoders are constructed for individual subjects and with limited data leading to restrictions on the types of models that can be utilized. Currently, the best performing decoders are typically linear models capable of utilizing rigid timing constraints with limited training data. Here we demonstrate the use of Long Short-Term Memory (LSTM) ne...
3 CitationsSource
Jul 1, 2016 in SPAWC (International Workshop on Signal Processing Advances in Wireless Communications)
#1K. P. ArunkumarH-Index: 1
#2Chandra R. Murthy (IISc: Indian Institute of Science)H-Index: 16
Last.Venkatesh Elango (UCSD: University of California, San Diego)H-Index: 1
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We present a scheme for joint sparse-channel recovery and data detection in cyclic-prefix orthogonal frequency division multiplex (CP-OFDM) communication over doubly-spread underwater acoustic channels. Inter-carrier interference (ICI), caused by path-dependent Doppler, results in a non-diagonal channel mixing matrix that makes recovery difficult. To combat the effect of ICI, we consider the sequence of observations from partial interval demodulators, and using a path-based channel model, cast t...
1 CitationsSource
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