Single Neuronal Dynamical System in Self-Feedbacked Hopfield Networks and Its Application in Image Encryption by Xitong Xu, Shengbo Chen

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A modified algorithm of Hopfield network to solve TSP(Hopfield网络解TSP的改进算法) by JIANGGuo-jun(姜国均)

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Dynamic elimination method for solving TSP by Hopfield network(Hopfield网络解旅行商问题的动态消元算法) by LUSheng-xun(陆生勋)

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Application of Artificial Neural Networks in Allocating Grant by Davood Hoseinpour, Khatere Hajinouri

Subjects: “…artificial neural network hopfield network…”
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Design and implementation of an integrated management system for discipline construction and postgraduate education in universities by Wang Chunxia

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Comparing Information-Theoretic Measures of Complexity in Boltzmann Machines by Maxinder S. Kanwal, Joshua A. Grochow, Nihat Ay

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Selective connectivity enhances storage capacity in attractor models of memory function by Facundo Emina, Facundo Emina, Emilio Kropff

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Optimal Load Dispatch in Competitive Electricity Market by Using Different Models of Hopfield Lagrange Network by Thanh Long Duong, Phuong Duy Nguyen, Van-Duc Phan, Dieu Ngoc Vo, Thang Trung Nguyen

Subjects: “…Lagrange Hopfield network…”
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An intelligent disease prediction system for psychological diseases by implementing hybrid hopfield recurrent neural network approach by Vikas Kamra, Praveen Kumar, Masoud Mohammadian

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Competition and cooperation in colour-word Stroop effect: An association approach by Yusoff, Nooraini, Grüning, André, Browne, Antony

“…Competition of stimuli occurs when the task is to name the colour for an incompatible colour-word and its colour (e.g. a word RED written in green), meanwhile the cooperation among stimuli can be observed when congruence (e.g. a word RED written in red) between both facilitates the response to the colour name. The Hopfield network is chosen for several reasons; we address the Stroop phenomenon as an association problem, the competition and cooperation of Stroop stimuli meets the pattern processing nature of the Hopfield network and the recall algorithm in Hopfield is biologically realistic.We have shown that, with a relatively simple but biologically plausible neural network of a single Hopfield network, our model is also able to predict the Stroop effect in comparison to the human performance.…”

Agent Based Modelling For New Technique In Neuro Symbolic Integration by Sathasivam, Saratha, Velavan, Muraly

“…This paper shows on developing agent based modelling for represent the performance of doing logic programming in Hopfield network by using a new activation function. The effects of the activation function on the performance of the neuro-symbolic integration are analyzed mathematically and compared with the existing method. …”
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Activation Functions in Neuro Symbolic Integration Using Agent Based Modelling by Sathasivam, Saratha, Velavan, Muraly

“…The resuls obtained showed that the Hyperbolic Tangent Activation function outperform other activation functions in doing logic programming in Hopfield network. The models developed by agent based modelling also support this theory.…”
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Quantum Hopfield neural network by Rebentrost, Patrick, Bromley, Thomas R., Weedbrook, Christian, Lloyd, Seth

“…Here we employ quantum algorithms for the Hopfield network, which can be used for pattern recognition, reconstruction, and optimization as a realization of a content-addressable memory system. …”
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Hybridised Network of Fuzzy Logic and a Genetic Algorithm in Solving 3-Satisfiability Hopfield Neural Networks by Farah Liyana Azizan, Saratha Sathasivam, Majid Khan Majahar Ali, Nurshazneem Roslan, Caicai Feng

“…This work proposed a new hybridised network of 3-Satisfiability structures that widens the search space and improves the effectiveness of the Hopfield network by utilising fuzzy logic and a metaheuristic algorithm. …”
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Study of recall time of associative memory in a memristive Hopfield neural network by Kong, Deyu, Hu, Shaogang, Wang, Junjie, Liu, Zhen, Chen, Tupei, Yu, Qi, Liu, Yang

“…In this paper, we study the recall time in a memristive Hopfield network (MHN) implemented with memristor-based synapses. …”
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Robust neural controller for robot manipulator by Lou, Jia Ming

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Building and developing agent based modelling for higher order logic in neuro symbolic integration. by Sathasivam, Saratha

“…We will test ABM for this upgraded method (higher order logic programming, Hopfield network, Boltzmann machine and activation function in some real life and simulated data sets. …”

Rock cavern design and performance auditing using neuralised rock engineering systems by Cai, Jungang

“…This Neuralised Rock Engineering Systems (NRES) approach integrates a data base and a data pre-processing program, the backpropagation networks, a Hopfield network and an expert system as different functional components. …”
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Neuro-Snake Pattern Recognition And Classification Using Gradiant Vector Flow (Gvf And Hnn) by Wissam Hassan Ali

“…Thesnakes can find the boundaries of objects so it is very accurate to take the shape of theobject wanted, that will eliminate the noise from the original image and reduce the biterror rate of the Hopfield network to 0.215 and overcome the oscillation state inrecognition of the entered pattern. …”
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Neuro Symbolic Integration and Agent Based Modelling by Sathasivam , Saratha, Velavan, Muraly

“…Meanwhile, neural networks, known as a mathematical model of neurons in the human brain, and have various abilities, and moreover, they also provide parallel computations and therefore can perform some calculations quicker than classical learning algorithms. Hopfield network is a feedback (recurrent) neural network, consisting of a set of N interconnected neurons which each neurons are linked to all others in all the directions. …”
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