Our approach is to use minimum probability flow (MPF) parameter estimation to deterministically fit very large Hopfield networks on windowed spike trains obtained from recordings of spontaneous activity of neurons in cat visual cortex. Examining the structure of the network memories over the spiking ...
Hopfield Neural Network(HNN) based parallel algorithm is presented for predicting the secondary structure of ribonucleic acids(RNA).The HNN here is used to find the near-maximum independent set of an adjacent graph made of RNA base pairs and then compute the stable secondary structure of RNA.. ...
A Hopfield network and a Boltzman machine represent examples of the former type while a recurrent neural network (RNN) is an example of the latter type of network (Fig. 12). Sign in to download full-size image Figure 12. Feedforward, Hopfield, and RNN. We now look at a feedforward ...
The results indicate that the proposed neural network generates good quality and solutions. 展开 关键词: Location-allocation Capacitated p-Median Problem (CPMP Neural Network Hopfield Network DOI: 10.1080/0013791X.2012.733488 被引量: 1 年份: 2012 ...
RNA secondary structure prediction is an important research field in bioinformatics.As one of the forecasting method,neural network has been widely used in protein structure prediction but very little in RNA secondary structure.The traditional prediction of RNA secondary structure using Hopfield neural net...
A qualitative analysis of Hopfield-type neural network models with lower block triangular interconnecting structure is presented. Such networks are viewed as interconnected systems and the results are phrased in terms of the qualitative properties of the subsystems of the networks and in terms of the...
The connection patterns of neural circuits in the brain form a complex network. Collective signalling within the network manifests as patterned neural activity and is thought to support human cognition and adaptive behaviour. Recent technological advance
An improved superconducting neural circuit and its application for a neural network solving a combinatorial optimization problem neural circuitits applicationWe have proposed a superconducting Hopfield-type neural network for solving the N-Queens problem which is one of combinatorial ... T Onomi,K Nakaj...
N. Estimating memory deterioration rates following neurodegeneration and traumatic brain injuries in a Hopfield network model. Front. Neurosci 11, 623 (2017). Article Google Scholar Burak, Y. & Fiete, I. R. Accurate path integration in continuous attractor network models of grid cells. PLoS ...
Active modules mark regions of a network that are most active during a given cellular or disease response and can identify important biomarkers, disease mechanisms and therapeutic targets. Conserved modules are revealed through the alignment or comparison of networks across multiple species. Such modules...