IEEE transactions on neural networks and learning systems
Nov 30, 2022
The Preisach model and the neural networks are two of the most popular strategies to model hysteresis. In this article, we first mathematically prove that the rate-independent Preisach model is actually a diagonal recurrent neural network (dRNN) with...
IEEE transactions on neural networks and learning systems
Nov 30, 2022
Deep neural networks include millions of learnable parameters, making their deployment over resource-constrained devices problematic. Sensitivity-based regularization of neurons (SeReNe) is a method for learning sparse topologies with a structure, ex...
IEEE transactions on neural networks and learning systems
Nov 30, 2022
Spiking neural networks (SNNs) contain more biologically realistic structures and biologically inspired learning principles than those in standard artificial neural networks (ANNs). SNNs are considered the third generation of ANNs, powerful on the ro...
IEEE transactions on neural networks and learning systems
Nov 30, 2022
Neuromorphic computing is a promising technology that realizes computation based on event-based spiking neural networks (SNNs). However, fault-tolerant on-chip learning remains a challenge in neuromorphic systems. This study presents the first scalab...
IEEE transactions on neural networks and learning systems
Nov 30, 2022
This article concerns with terminal recurrent neural network (RNN) models for time-variant computing, featuring finite-valued activation functions (AFs), and finite-time convergence of error variables. Terminal RNNs stand for specific models that adm...
Neural systems are networks, and strategic comparisons between multiple networks are a prevalent task in many research scenarios. In this study, we construct a statistical test for the comparison of matrices representing pairwise aspects of neural ne...
Advanced materials (Deerfield Beach, Fla.)
Nov 29, 2022
Spiking neural network (SNN), where the information is evaluated recurrently through spikes, has manifested significant promises to minimize the energy expenditure in data-intensive machine learning and artificial intelligence. Among these applicatio...
Environmental monitoring and assessment
Nov 24, 2022
Recent developments of heterogeneous advanced oxidation for refractory organic contaminants and catalysts made of solid waste have attracted much attention. In this work, waste printed circuit board (wPCB) was used for catalytic degradation of simula...
BACKGROUND: Synapses are the connections between neurons in the central nervous system (CNS) or between neurons and other excitable cells in the peripheral nervous system (PNS), where electrical or chemical signals rapidly travel through one cell to ...
This article aims at analyzing and designing the multivalued high-capacity-associative memories based on recurrent neural networks with both asynchronous and distributed delays. In order to increase storage capacities, multivalued activation function...
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