Quantitatively Evaluating the Effect of Read Noise in Memristive Hopfield Network on Solving Traveling Salesman Problem
Sign Up to like & getrecommendations! Published in 2020 at "IEEE Electron Device Letters"
DOI: 10.1109/led.2020.3021593
Abstract: Hopfield neural network, as a recurrent neural network, has been widely used to solve non-deterministic polynomial time-hard problems. However, the network tends to get trapped into local minima and thus converge to sub-optimal solutions. In… read more here.
Keywords: read noise; hopfield network; memristive hopfield; noise memristive ... See more keywords
A Feed-Forward Neural Network for Increasing the Hopfield-Network Storage Capacity
Sign Up to like & getrecommendations! Published in 2022 at "International journal of neural systems"
DOI: 10.1142/s0129065722500277
Abstract: In the hippocampal dentate gyrus (DG), pattern separation mainly depends on the concepts of 'expansion recoding', meaning random mixing of different DG input channels. However, recent advances in neurophysiology have challenged the theory of pattern… read more here.
Keywords: neural network; network; hopfield network; storage capacity ... See more keywords
Optimal CNN-Hopfield Network for Pattern Recognition Based on a Genetic Algorithm
Sign Up to like & getrecommendations! Published in 2022 at "Algorithms"
DOI: 10.3390/a15010011
Abstract: Convolutional neural networks (CNNs) have powerful representation learning capabilities by automatically learning and extracting features directly from inputs. In classification applications, CNN models are typically composed of: convolutional layers, pooling layers, and fully connected (FC)… read more here.
Keywords: cnn hopfield; optimal cnn; genetic algorithm; hopfield network ... See more keywords