We propose the architecture of a novel robot system merging biological and artificial intelligence based on a neural controller connected to an external agent. We initially built a framework that connected the dissociated neural network to a mobile r...
In this paper, a two-layer network is built to simulate the mechanism of visual selection and shifting based on the mapping dynamic model for instantaneous frequency. Unlike the differential equation model using limit cycle to simulate neuron oscilla...
We propose a biologically plausible architecture for unsupervised ensemble learning in a population of spiking neural network classifiers. A mixture of experts type organisation is shown to be effective, with the individual classifier outputs combine...
Neural networks : the official journal of the International Neural Network Society
Sep 30, 2016
Firing-rate dynamics have been hypothesized to mediate inter-neural information transfer in the brain. While the Hebbian paradigm, relating learning and memory to firing activity, has put synaptic efficacy variation at the center of cortical plastici...
The separation of input patterns received from the entorhinal cortex (EC) by the dentate gyrus (DG) is a well-known critical step of information processing in the hippocampus. Although the role of interneurons in separation pattern efficiency of the ...
Neural networks : the official journal of the International Neural Network Society
Sep 19, 2016
This paper deals with the H state estimation problem for a class of discrete-time neural networks with stochastic delays subject to state- and disturbance-dependent noises (also called (x,v)-dependent noises) and fading channels. The time-varying sto...
There is a commonality among contagious diseases, tweets, and neuronal firings that past events facilitate the future occurrence of events. The spread of events has been extensively studied such that the systems exhibit catastrophic chain reactions i...
Spiking neural P systems are a new candidate in spiking neural network models. By using neuron division and budding, such systems can generate/produce exponential working space in linear computational steps, thus provide a way to solve computational ...
Neural networks : the official journal of the International Neural Network Society
Sep 10, 2016
This paper investigates the exponential synchronization of delayed memristor-based neural networks (MNNs) with discontinuous activation functions. Based on the framework of Filippov solution and differential inclusion theory, using new analytical tec...
IEEE transactions on biomedical circuits and systems
Sep 9, 2016
We present results from a new approach to learning and plasticity in neuromorphic hardware systems: to enable flexibility in implementable learning mechanisms while keeping high efficiency associated with neuromorphic implementations, we combine a ge...