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A Sparsity-Adapted Hardware Implementation of SNN for Cortical Spike Trains Decoding.

, , , , , , и . BioCAS, стр. 1-4. IEEE, (2023)

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Liu Liu

Liu Liu

Liu Liu

Jiaru Liu

Kang Liu

 

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Transfer Learning based Efficient Schizophrenia Classification on Electroencephalogram (EEG) Signals: A Cross-Dataset Study., , , , , , и . ICBBT, стр. 143-148. ACM, (2023)Decoding Finger Velocity from Cortical Spike Trains with Recurrent Spiking Neural Networks., , , , , и . BioCAS, стр. 1-5. IEEE, (2024)Copyright-Certified Distillation Dataset: Distilling One Million Coins into One Bitcoin with Your Private Key., , и . AAAI, стр. 6458-6466. AAAI Press, (2023)Deniable Diffusion Generative Steganography., , и . ICME, стр. 67-71. IEEE, (2023)A Sparsity-Adapted Hardware Implementation of SNN for Cortical Spike Trains Decoding., , , , , , и . BioCAS, стр. 1-4. IEEE, (2023)An Improved PSO Algorithm with an Area-Oriented Learning Strategy., , , , и . ICIC (3), том 11645 из Lecture Notes in Computer Science, стр. 640-650. Springer, (2019)Modularity Facilitates Classification Performance of Spiking Neural Networks for Decoding Cortical Spike Trains., , , , , , и . EMBC, стр. 1-4. IEEE, (2023)motorSRNN: A spiking recurrent neural network inspired by brain topology for the effective and efficient decoding of cortical spike trains., , , , , , , , , и . Biomed. Signal Process. Control., (2025)