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Wireless EEG System Achieving High Throughput and Reduced Energy Consumption Through Lossless and Near-Lossless Compression.

, , , , , , , , and . IEEE Trans. Biomed. Circuits Syst., 12 (1): 231-241 (2018)

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Exploring fpga Optimizations to Compute Sparse Numerical Linear Algebra Kernels., , , and . ARC, volume 12083 of Lecture Notes in Computer Science, page 258-268. Springer, (2020)Understanding the Performance of Elementary NLA Kernels in FPGAs., , , and . IPDPS Workshops, page 479-482. IEEE, (2020)Time-Power-Energy Balance of blas Kernels in Modern fpgas., , , and . CARLA, volume 1660 of Communications in Computer and Information Science, page 78-89. Springer, (2022)Unleashing the computational power of FPGAs to efficiently perform SPMV operation., , and . SCCC, page 1-8. IEEE, (2021)A 64-channel wireless EEG recording system for wearable applications., , , , , and . LASCAS, page 1-4. IEEE, (2018)A Framework to Compare Estimated and Measured Power Consumption on FPGAs., , and . J. Low Power Electron., 15 (4): 329-337 (2019)A Low Cost System for Self Measurements of Power Consumption in Field Programmable Gate Arrays., , , and . J. Low Power Electron., 13 (1): 1-9 (2017)Wireless EEG System Achieving High Throughput and Reduced Energy Consumption Through Lossless and Near-Lossless Compression., , , , , , , , and . IEEE Trans. Biomed. Circuits Syst., 12 (1): 231-241 (2018)Tracking the pipelining-power rule along the FPGA technical literature., , and . FPGAworld, page 9:1-9:5. ACM, (2013)Wearable EEG via lossless compression., , , , , , , , and . EMBC, page 1995-1998. IEEE, (2016)