Clockless FPGA circuits produce autonomous spiking neuron networks that achieve competitive audio classification accuracy with significantly lower power than conventional digital implementations.
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Spin wave-based physical reservoir computing achieves 85.8% speaker classification accuracy without cochleagram preprocessing.
Non-steady-state chemical charge transport dynamics integrated into reservoir computing enable waveform recognition, voice identification, and chaos prediction, with performance governed by frequency alignment that functions as a chemically-tuned band-pass filter.
citing papers explorer
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Scalable neuromorphic computing from autonomous spiking dynamics in a clockless reconfigurable chip
Clockless FPGA circuits produce autonomous spiking neuron networks that achieve competitive audio classification accuracy with significantly lower power than conventional digital implementations.
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Spoken Digit Recognition and Speaker Classification by Nonlinear Interfered Spin Wave-Based Physical Reservoir Computing
Spin wave-based physical reservoir computing achieves 85.8% speaker classification accuracy without cochleagram preprocessing.
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Exploring Non-Steady-State Charge Transport Dynamics in Information Processing: Insights from Reservoir Computing
Non-steady-state chemical charge transport dynamics integrated into reservoir computing enable waveform recognition, voice identification, and chaos prediction, with performance governed by frequency alignment that functions as a chemically-tuned band-pass filter.