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EchoBay: Design and Optimization of Echo State Networks under Memory and Time Constraints.

, , , , and . ACM Trans. Archit. Code Optim., 17 (3): 22:1-22:24 (2020)

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EchoBay: Design and Optimization of Echo State Networks under Memory and Time Constraints., , , , and . ACM Trans. Archit. Code Optim., 17 (3): 22:1-22:24 (2020)Control of Power Electronics through a Photonic Bus: Feasibility and Prospects., , , , , , , and . J. Sens. Actuator Networks, 7 (4): 53 (2018)Continuous Blood Pressure Estimation Through Optimized Echo State Networks., , , , and . ICANN (Workshop), volume 11731 of Lecture Notes in Computer Science, page 48-61. Springer, (2019)Efficient Embedded Machine Learning applications using Echo State Networks., , , , and . DATE, page 1299-1302. IEEE, (2020)lightweight autonomous bayesian optimization of Echo-State Networks., , and . ESANN, (2019)Robustness of Surface EMG Classifiers with Fixed-Point Decomposition on Reconfigurable Architecture., , , and . IPDPS Workshops, page 146-153. IEEE Computer Society, (2018)A Hardware Acceleration for Surface EMG Non-Negative Matrix Factorization., , , and . IPDPS Workshops, page 168-174. IEEE Computer Society, (2017)Post-Training Quantization with Low-precision Minifloats and Integers on FPGAs., , , , , , and . CoRR, (2023)FPGA-based muscle synergy extraction for surface EMG gesture classification., , , , , and . BioCAS, page 1-4. IEEE, (2017)Electric Vehicle Powertrain and Fuzzy Control Multi-Objective Optimization, Considering Dual Hybrid Energy Storage Systems., , , and . IEEE Trans. Veh. Technol., 69 (4): 3773-3782 (2020)