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Found 5 papers, 3 papers with code
Neuromorphic Keyword Spotting with Pulse Density Modulation MEMS Microphones
The Keyword Spotting (KWS) task involves continuous audio stream monitoring to detect predefined words, requiring low energy devices for continuous processing.
Accelerating SNN Training with Stochastic Parallelizable Spiking Neurons
In this paper, we propose the Stochastic Parallelizable Spiking Neuron (SPSN) to overcome the sequential training limitation of LIF neurons.
Hardware-aware Training Techniques for Improving Robustness of Ex-Situ Neural Network Transfer onto Passive TiO2 ReRAM Crossbars
Passive resistive random access memory (ReRAM) crossbar arrays, a promising emerging technology used for analog matrix-vector multiplications, are far superior to their active (1T1R) counterparts in terms of the integration density.
Efficient spike encoding algorithms for neuromorphic speech recognition
Finally, we show that several encoding methods result in improved performance over the conventional deep learning baseline in certain cases, further demonstrating the power of spike encoding algorithms in the encoding of real-valued signals and that neuromorphic implementation has the potential to outperform state of the art techniques.
Robust learning from corrupted EEG with dynamic spatial filtering
Building machine learning models using EEG recorded outside of the laboratory setting requires methods robust to noisy data and randomly missing channels.
