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A High-level Implementation Framework for Non-Recurrent Artificial Neural Networks on FPGA.

, , , , , and . PRIME, page 77-80. IEEE, (2019)

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A High-level Implementation Framework for Non-Recurrent Artificial Neural Networks on FPGA., , , , , and . PRIME, page 77-80. IEEE, (2019)Chained Compressed Sensing: A Blockchain-Inspired Approach for Low-Cost Security in IoT Sensing., , , , and . IEEE Internet of Things Journal, 6 (4): 6465-6475 (2019)Disturbance Rejection With Rakeness-based Compressed Sensing: Method and Application to Baseline/Powerline Mitigation in ECGs., , , , and . ISCAS, page 1-5. IEEE, (2018)An MCU Implementation of PCA/PSA Streaming Algorithms for EEG Features Extraction., , , , , and . BioCAS, page 1-5. IEEE, (2021)Embedding principal component analysis for data reduction in structural health monitoring on low-cost IoT gateways., , , and . CF, page 235-239. ACM, (2019)Resource Redistribution in Internet of Things applications by Compressed Sensing: A Survey., , , , , and . ISCAS, page 1-5. IEEE, (2018)Chained Compressed Sensing for Iot Node Security., , , , and . ICASSP, page 7580-7584. IEEE, (2019)Rakeness-based Compressed Sensing of Surface ElectroMyoGraphy for Improved Hand Movement Recognition in the Compressed Domain., , , , and . BioCAS, page 1-4. IEEE, (2018)Administering Quality-Energy Trade-Off in IoT Sensing Applications by Means of Adapted Compressed Sensing., , , , and . IEEE J. Emerg. Sel. Topics Circuits Syst., 8 (4): 895-907 (2018)Projected-Gradient-Descent in Rakeness-Based Compressed Sensing with Disturbance Rejection., , , , , and . NGCAS, page 78-81. IEEE, (2018)