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.
(4 9 ) Lukoševičius, M.; Jaeger, H., Reservoir computing approaches to recurrent neural network training
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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.