Neural networks : the official journal of the International Neural Network Society
Aug 10, 2022
Backpropagation (BP) algorithm is one of the most basic learning algorithms in deep learning. Although BP has been widely used, it still suffers from the problem of easily falling into the local minima due to its gradient dynamics. Inspired by the fa...
Journal of computational neuroscience
Aug 10, 2022
An important function of the brain is to predict which stimulus is likely to occur based on the perceived cues. The present research studied the branching behavior of a computational network model of populations of excitatory and inhibitory neurons, ...
Proceedings of the National Academy of Sciences of the United States of America
Aug 10, 2022
We propose that coding and decoding in the brain are achieved through digital computation using three principles: relative ordinal coding of inputs, random connections between neurons, and belief voting. Due to randomization and despite the coarsenes...
Advanced science (Weinheim, Baden-Wurttemberg, Germany)
Aug 4, 2022
Owing to programmable nonlinear dynamics, magnetic domain wall (DW)-based devices can be configured to function as spintronic neurons, promising to execute sophisticated tasks as a human brain. Developing energy-efficient, CMOS compatible, reliable, ...
IEEE transactions on pattern analysis and machine intelligence
Aug 4, 2022
Deep neural networks are trained so as to achieve a kind of the maximum overall accuracy through a learning process using given training data. Therefore, it is difficult to fix them to improve the accuracies of specific problematic classes or classes...
Neural networks : the official journal of the International Neural Network Society
Aug 3, 2022
The human hippocampus possesses "concept cells", neurons that fire when presented with stimuli belonging to a specific concept, regardless of the modality. Recently, similar concept cells were discovered in a multimodal network called CLIP (Radford e...
IEEE transactions on neural networks and learning systems
Aug 3, 2022
Dropout and DropConnect are two techniques to facilitate the regularization of neural network models, having achieved the state-of-the-art results in several benchmarks. In this paper, to improve the generalization capability of spiking neural networ...
IEEE transactions on neural networks and learning systems
Aug 3, 2022
The performance of a biologically plausible spiking neural network (SNN) largely depends on the model parameters and neural dynamics. This article proposes a parameter optimization scheme for improving the performance of a biologically plausible SNN ...
PLoS computational biology
Aug 1, 2022
Brain rhythms emerge from synchronization among interconnected spiking neurons. Key properties of such rhythms can be gleaned from the phase-resetting curve (PRC). Inferring the PRC and developing a systematic phase reduction theory for large-scale b...
ISA transactions
Jul 20, 2022
This paper studies the fixed-time projective synchronization problem for a class of delayed memristive neural networks via aperiodically semi-intermittent switching control. Instead of using the common traditional controller containing two power expo...