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Found 6 papers, 1 papers with code
Recovering Arrhythmic EEG Transients from Their Stochastic Interference
Traditionally, the neuronal dynamics underlying electroencephalograms (EEG) have been understood as arising from \textit{rhythmic oscillators with varying degrees of synchronization}.
Computation harvesting in road traffic dynamics
Owing to recent advances in artificial intelligence and internet of things (IoT) technologies, collected big data facilitates high computational performance, while its computational resources and energy cost are large.
Decentralized Algorithms for Consensus-Based Power Packet Distribution
We also discuss the mechanism of the decentralized algorithm for the operation of power packets and reveal the feasibility of the given control method and application by forming biased power flows on the consensus-based distribution.
Road traffic reservoir computing
Reservoir computing derived from recurrent neural networks is more applicable to real world systems than deep learning because of its low computational cost and potential for physical implementation.
Effect of shapes of activation functions on predictability in the echo state network
We investigate prediction accuracy for time series of Echo state networks with respect to several kinds of activation functions.
Generative adversarial network-based approach to signal reconstruction from magnitude spectrograms
In this paper, we address the problem of reconstructing a time-domain signal (or a phase spectrogram) solely from a magnitude spectrogram.
