AIMC Topic: Neurons

Clear Filters Showing 511 to 520 of 1455 articles

BackEISNN: A deep spiking neural network with adaptive self-feedback and balanced excitatory-inhibitory neurons.

Neural networks : the official journal of the International Neural Network Society
Spiking neural networks (SNNs) transmit information through discrete spikes that perform well in processing spatial-temporal information. Owing to their nondifferentiable characteristic, difficulties persist in designing SNNs that deliver good perfor...

Sequence Learning in a Single Trial: A Spiking Neurons Model Based on Hippocampal Circuitry.

IEEE transactions on neural networks and learning systems
In contrast with our everyday experience using brain circuits, it can take a prohibitively long time to train a computational system to produce the correct sequence of outputs in the presence of a series of inputs. This suggests that something import...

BiCoSS: Toward Large-Scale Cognition Brain With Multigranular Neuromorphic Architecture.

IEEE transactions on neural networks and learning systems
The further exploration of the neural mechanisms underlying the biological activities of the human brain depends on the development of large-scale spiking neural networks (SNNs) with different categories at different levels, as well as the correspond...

How to Analyze the Neurodynamic Characteristics of Pulse-Coupled Neural Networks? A Theoretical Analysis and Case Study of Intersecting Cortical Model.

IEEE transactions on cybernetics
The intersecting cortical model (ICM), initially designed for image processing, is a special case of the biologically inspired pulse-coupled neural-network (PCNN) models. Although the ICM has been widely used, few studies concern the internal activit...

A Sparse and Spike-Timing-Based Adaptive Photoencoder for Augmenting Machine Vision for Spiking Neural Networks.

Advanced materials (Deerfield Beach, Fla.)
The representation of external stimuli in the form of action potentials or spikes constitutes the basis of energy efficient neural computation that emerging spiking neural networks (SNNs) aspire to imitate. With recent evidence suggesting that inform...

The minimum regret path problem on stochastic fuzzy time-varying networks.

Neural networks : the official journal of the International Neural Network Society
In this paper, we introduce a stochastic fuzzy time-varying minimum regret path problem (SFTMRP), which combines the characteristics of the min-max regret path and maximum probability path as a variant of the stochastic fuzzy time-varying shortest pa...

Cardinality-constrained portfolio selection via two-timescale duplex neurodynamic optimization.

Neural networks : the official journal of the International Neural Network Society
This paper addresses portfolio selection based on neurodynamic optimization. The portfolio selection problem is formulated as a biconvex optimization problem with a variable weight in the Markowitz risk-return framework. In addition, the cardinality-...

Multimodal Orbital Angular Momentum Data Model Based on Mechanically Reconfigurable Arrays and Neural Networks.

Computational intelligence and neuroscience
Multimodal orbital angular momentum is a research hotspot in the field of electromagnetic wave communication. How to accurately detect and identify multimodal orbital angular momentum data is a current academic problem. Based on the theory of mechani...

Sequence learning, prediction, and replay in networks of spiking neurons.

PLoS computational biology
Sequence learning, prediction and replay have been proposed to constitute the universal computations performed by the neocortex. The Hierarchical Temporal Memory (HTM) algorithm realizes these forms of computation. It learns sequences in an unsupervi...

Error-based or target-based? A unified framework for learning in recurrent spiking networks.

PLoS computational biology
The field of recurrent neural networks is over-populated by a variety of proposed learning rules and protocols. The scope of this work is to define a generalized framework, to move a step forward towards the unification of this fragmented scenario. I...