Java classes for Hopfield neural networks
Open quantum generalisation of Hopfield neural networks
... In order to make our ideas concrete we introduce a generalisation based on OQSs of one of the most studied NN systems, the Hopfield model [22] (see Fig. 1). The dissipative part of the dynamics corresponds to the ...
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Convergence of discrete delayed Hopfield neural networks
... artificial neural networks have been extensively studied and ...are Hopfield-types neural networks, which have been ...two Hopfield-types neural ...discrete ...
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Hopfield Neural Networks for Aircrafts’ Enroute Sectoring: KRISHAN-HOPES
... research. Hopfield neural networks or simply Hopfield nets, a widely used popular category of feedback neural network or recurrent neural networks may play a very ...
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Incorporating web analysis into neural networks: An example in hopfield net searching
... the Hopfield net spreading activation did not suffer from such problem because it incorporated Web link analysis and domain- specific content analysis into the ...the Hopfield net also prevented the ...
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Stochastic stability analysis of fuzzy Hopfield neural networks with time-varying delays
... fuzzy neural networks with time-varying delay, such as stochastic fuzzy cellular neural networks and stochastic fuzzy BAM neural networks, ...
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A New OFDMA Scheduler for Delay Sensitive Traffic Based on Hopfield Neural Networks
... 2. SYSTEM MODEL The considered DRA problem assumes a set of N users, i = 1, . . . ,N, with their corresponding queues located at the base station of the access network which contains the pack- ets pending to be ...
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Programming Neural Networks in Java JeffHeaton pdf
... using the parallel properties of superposition all possibilities can be computed simultaneously. If the Church-Turing thesis is indeed true for all quantum computers is in some doubt. The quantum computer previously ...
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Enhanced Hopfield Neural Networks With Artificial Immune System Algorithm For Satisfiability Logic Programming
... three common methods, penalty functions, Lagrange multipliers, and primal and dual methods to construct an energy function (Pinkas, 1991). Moreover, the HNN mini- mizes Lyapunov energy by utilizing the physical Ising ...
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CLASSIFICATION OF STANDARD ORAL CANCER USING TEXTURAL ANALYSIS AND HYBRID HOPFIELD NEURAL NETWORKS
... ABSTRACT Oral cancer is a chief health issues in the United States and worldwide. The oral cancer cell detection and segmentation stages are greatly influenced by the intensity distribution, contrast, and clarity of the ...
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Global exponential stability of impulsive high-order Hopfield type neural networks with delays
... Introduction Hopfield neural networks have been extensively studied and developed in recent years, and there has been considerable attention in the literature on Hopfield neural ...
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Robust Exponential Memory in Hopfield Networks
... The Hopfield recurrent neural network is a classical auto-associative model of memory, in which collections of symmetrically coupled McCulloch–Pitts binary neurons interact to perform emergent ...of ...
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Solving uncapacitated hub location problem using Hopfield-Tank type artificial neural networks
... telecommunication networks, the cost of carrying a unit of traffic between two points decreases as the capacity of the connection joining the two points ...delivery networks, large telecommunication ...
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A User-Centric Approach for Dynamic Resource Allocation in CDMA systems based on Hopfield Neural Networks
... different classes of users with different Contracted User Profiles are introduced and a Hopfield Neural Network optimization methodology is used under both user and network ...
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Optimizing hopfield neural network for super-resolution mapping
... cover classes. Hopfield neural network ( HNN ) is a popular approach in SRM ...Four classes of land covers such as vegetation, water bodies, roads, and buildings are used in this ...
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THE HOPFIELD NEURAL NETWORK IN THE ASPECT OF THE STABILIZATION OF THE DISPLACEMENT PHENOMENON
... The Hopfield neural network also called the Hopfield model is a dynamic system dissipative in charakter ...these networks have been used in practice to build integrated circuits physically ...
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IMPORTANCE AND USES OF HOPFIELD NEURAL NETWORK AND PATTERN STORAGE
... The evolutionary training approach is attractive because it can handle the global search problem better. It does not depend on gradient information of the error (or fitness) function and thus is particularly appealing ...
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New Results of Global Asymptotical Stability for Impulsive Hopfield Neural Networks with Leakage Time Varying Delay
... impulsive Hopfield neural networks with leakage time-varying delay by model transformation technique and a certain Lyapunov-Krasovskii functional combined with LMI technique and construct a new ...
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A delay-dividing approach to robust stability of uncertain stochastic complex-valued Hopfield delayed neural networks
... neural networks. Specifically, the uncertain stochastic complex-valued Hopfield neural network (USCVHNN) with time delay is ...complex-valued neural network (CVNN) into two parts, ...
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Anti periodic solution for impulsive high order Hopfield neural networks with time varying delays in the leakage terms
... Abstract This paper presents new results on anti-periodic solutions for impulsive high-order Hopfield neural networks with time-varying delays in the leakage terms. By employing a novel proof, some criteria ...
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Superresolution mapping using a hopfield neural network with fused images
... cover classes within a pixel based on the proportion images produced by soft ...[12], Hopfield neural net- work (HNN) optimization [13]–[17], two-point histrogram op- timization [18], genetic ...
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