IEEE transactions on neural networks and learning systems
Oct 27, 2022
Spiking neural networks (SNNs) based on the leaky integrate and fire (LIF) model have been applied to energy-efficient temporal and spatiotemporal processing tasks. Due to the bioplausible neuronal dynamics and simplicity, LIF-SNN benefits from event...
Biologically plausible computational modeling of visual perception has the potential to link high-level visual experiences to their underlying neurons' spiking dynamic. In this work, we propose a neuromorphic (brain-inspired) Spiking Neural Network (...
IEEE transactions on visualization and computer graphics
Oct 26, 2022
Deep reinforcement learning (DRL) targets to train an autonomous agent to interact with a pre-defined environment and strives to achieve specific goals through deep neural networks (DNN). Recurrent neural network (RNN) based DRL has demonstrated supe...
Neural networks : the official journal of the International Neural Network Society
Oct 20, 2022
Inferring the connectivity of biological neural networks from neural activation data is an open problem. We propose that the analogous problem in artificial neural networks is more amenable to study and may illuminate the biological case. Here, we st...
Computational intelligence and neuroscience
Oct 20, 2022
With the development of neuromorphic computing, more and more attention has been paid to a brain-inspired spiking neural network (SNN) because of its ultralow energy consumption and high-performance spatiotemporal information processing. Due to the d...
International journal of neural systems
Oct 17, 2022
Spiking neural P systems (SN P systems), inspired by biological neurons, are introduced as symbolical neural-like computing models that encode information with multisets of symbolized spikes in neurons and process information by using spike-based rew...
Artificial neural networks have demonstrated superiority over traditional computing architectures in tasks such as pattern classification and learning. However, they do not measure uncertainty in predictions, and hence they can make wrong predictions...
Computational intelligence and neuroscience
Oct 13, 2022
Spiking neural network (SNN) has attracted extensive attention in the field of machine learning because of its biological interpretability and low power consumption. However, the accuracy of pattern recognition cannot completely surpass deep neural n...
Sequential behavior unfolds both in space and in time. The same spatial trajectory can be realized in different manners in the same overall time by changing instantaneous speeds. The current research investigates how speed profiles might be given beh...
IEEE transactions on biomedical circuits and systems
Oct 12, 2022
Human brain cortex acts as a rich inspiration source for constructing efficient artificial cognitive systems. In this paper, we investigate to incorporate multiple brain-inspired computing paradigms for compact, fast and high-accuracy neuromorphic ha...
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