Due to potential conflicts of constraints for sequencing optimization from the imbedding of precedence relationships, the soft computing ability of neural networks must be utilized in this refining procedure. This paper models the problem that allows an analogy to be conducted between finding the best ...
Neurons: The Hopfield network has a finite set of neurons x(i),1≤i≤N, which serve as processing units. Each neuron has a value (or state) at time t described by xt(i). A neuron in the Hopfield net has one of the two states, either -1 or +1; that is, xt(i)∈{-1,+1}...
but will stick to softmax in this post). The term “Fully Connected” implies that every neuron in the previous layer is connected to every neuron on the next layer. I recommendreading this postif you are
Control of nuclear research reactors based on a generalized Hopfield neural network. Intelligent Automation and Soft Computing . 2010; 16 (1):39–60.Humberto Pérez-Cruz J., Poznyak A. Control of nuclear research reactors based on a generalized Hopfield neural network. Intelligent Automation and ...
An important difference between brains and deep neural networks is the way they learn. Nervous systems learn online where a stream of noisy data points are presented in a non-independent, identically distributed way. Further, synaptic plasticity in the b
energyfunctionisthusgiveninasimplerformula,fewerparametersandhighercomputingeficiency.Meanwhile,themutation operatorofgeneticalgorithmisappliedinthisHNN,whichmaketheHNNcanserf-adjustundersomeconditions.Moreover, greedyalgorithmanddamtransformationtechniquealeintroducedinthiskindHNN,whichcanmakeHNNescapesfromthe ...
International Journal on Soft ComputingT. P. Singh and S. Jabin, "Evolving Connection Weights for Pattern Storage and Recall in Hopfield Model of Feedback Neural Network Using Genetic Algorithm," International Journal on Soft Computing (IJSC), Vol. 3(2), pp. 55-62, May 2012....
In order to explore chaotic systems with complex topological structure, this study focuses on the fusion of memristor and neural network in real physical models. This article innovatively combines local active memristors with Hopfield neural networks, constructing a novel coexisting dual-vortex memristive...
Sirinaovakul, The best-so-far selection in artificial bee colony algorithm, Applied Soft Computing 11(2), (2011), 2888-2901. D. Karaboga, and B. Basturk, A powerful and efficient algorithm for numerical function optimization: artificial bee colony (ABC) algorithm, Journal of global ...
(2006). A Novel Approach to Image Reconstruction from Discrete Projections Using Hopfield-Type Neural Network. In: Rutkowski, L., Tadeusiewicz, R., Zadeh, L.A., Żurada, J.M. (eds) Artificial Intelligence and Soft Computing – ICAISC 2006. ICAISC 2006. Lecture Notes in Computer Science...