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Convergence properties of a modified Hopfield-Tank model
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What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
inferredcites →https://doi.org/10.1007/bf00197648openalex-snapshot
On problem solving with Hopfield neural networks
inferredcites →https://doi.org/10.1007/bf00336888openalex-snapshot
Solving a combinatorial problem via self-organizing process: An application of the Kohonen algorithm to the traveling salesman problem
inferredcites →https://doi.org/10.1007/bf00337288openalex-snapshot
Self-organized formation of topologically correct feature maps
inferredcites →https://doi.org/10.1007/bf00339943openalex-snapshot
“Neural” computation of decisions in optimization problems
inferredcites →https://doi.org/10.1007/bf00363956openalex-snapshot
On the stability of the Travelling Salesman Problem algorithm of Hopfield and Tank
inferredcites →https://doi.org/10.1038/326689a0openalex-snapshot
An analogue approach to the travelling salesman problem using an elastic net method
inferredcites →https://doi.org/10.1073/pnas.81.10.3088openalex-snapshot
Neurons with graded response have collective computational properties like those of two-state neurons.
inferredcites →https://doi.org/10.1126/science.220.4598.671openalex-snapshot
Optimization by Simulated Annealing
inferredcites →https://doi.org/10.1137/1026105openalex-snapshot
The N -City Travelling Salesman Problem: Statistical Mechanics and the Metropolis Algorithm
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
inferred← citeshttps://doi.org/10.1007/bf00201419openalex-snapshot
Solving the N-Queens problem with a binary Hopfield-type network
inferred← citeshttps://doi.org/10.1007/bf00203674openalex-snapshot
A neural network designed to solve the N-Queens Problem
inferred← citeshttps://doi.org/10.1007/s00422-024-01002-0openalex-snapshot
Beyond the Nobel prizes: towards new synergies between Computational Neuroscience and Artificial Intelligence
inferred← citeshttps://doi.org/10.1007/s11571-010-9142-9openalex-snapshot
Generalization of learning by synchronous waves: from perceptual organization to invariant organization
inferred← citeshttps://doi.org/10.1016/0020-0255(96)00118-1openalex-snapshot
Combinatorial optimization by Hopfield networks using adjusting neurons
inferred← citeshttps://doi.org/10.1016/0305-0548(92)90044-6openalex-snapshot
Neural network methods in combinatorial optimization
inferred← citeshttps://doi.org/10.1016/0893-6080(96)00017-2openalex-snapshot
An Investigation into the Improvement of Local Minima of the Hopfield Network
inferred← citeshttps://doi.org/10.1016/j.physleta.2019.126143openalex-snapshot
Stochastic resonance in Hopfield neural networks for transmitting binary signals
inferred← citeshttps://doi.org/10.1016/s0094-114x(98)00035-4openalex-snapshot
An artificial neural network approach to mechanism kinematic chain isomorphism identification
inferred← citeshttps://doi.org/10.1016/s0278-6125(00)80001-1openalex-snapshot
Disassembly sequence generation using a neural network approach
inferred← citeshttps://doi.org/10.1016/s0925-2312(01)00580-xopenalex-snapshot
An automata network for performing combinatorial optimization
inferred← citeshttps://doi.org/10.1016/s0925-2312(99)00132-0openalex-snapshot
Optimization with the Hopfield network based on correlated noises: Experimental approach
inferred← citeshttps://doi.org/10.1016/s0952-1976(01)00013-6openalex-snapshot
Using Hopfield neural networks for operational sequencing for prismatic parts on NC machines
inferred← citeshttps://doi.org/10.1109/ibcast.2012.6177538openalex-snapshot
Critical analysis of hopfield's neural network model for TSP and its comparison with heuristic algorithm for shortest path computation
inferred← citeshttps://doi.org/10.1109/ibcast.2012.6177539openalex-snapshot
Critical analysis of hopfield's neural network model and heuristic algorithm for shortest path computation for routing in computer networks
inferred← citeshttps://doi.org/10.1109/icc.1995.524472openalex-snapshot
A neural network shortest path algorithm for routing in packet-switched communication networks
inferred← citeshttps://doi.org/10.1109/icnn.1994.375001openalex-snapshot
Impact of energy function on a neural network model for optimization problems
inferred← citeshttps://doi.org/10.1109/icnn.1994.375002openalex-snapshot
An investigation of the precision impact on the Hopfield-Tank neural network model for the TSP
inferred← citeshttps://doi.org/10.1109/icnn.1994.375019openalex-snapshot
A hierarchical approach for solving large-scale traveling salesman problem
inferred← citeshttps://doi.org/10.1109/icnn.1995.487829openalex-snapshot
Using the Hopfield neural network with mean field annealing to solve the shortest path problem in a communication network
inferred← citeshttps://doi.org/10.1109/icsmc.1995.538235openalex-snapshot
Using the Hopfield model with mean field annealing to solve the routing problem in packet-switched communication networks
inferred← citeshttps://doi.org/10.1109/ijcnn.1993.716858openalex-snapshot
Machine and bit precision influence on the Hopfield-Tank model for the TSP
inferred← citeshttps://doi.org/10.1109/tsp.2012.6256276openalex-snapshot
Neural networks based Physical Cell Identity assignment for self organized 3GPP Long Term Evolution
inferred← citeshttps://doi.org/10.11601/ijates.v2i3.17openalex-snapshot
Neural Networks Based Physical Cell Identity Assignment for Self Organized 3GPP Long Term Evolution
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Computer comparison of design knowledge
inferred← citeshttps://doi.org/10.14311/nnw.2017.27.016openalex-snapshot
OPTIMIZATION OF N + 1 QUEENS PROBLEM USING DISCRETE NEURAL NETWORK
inferred← citeshttps://doi.org/10.1515/dema-1996-0126openalex-snapshot
SOLVING THE TRAVELLING SALESMAN PROBLEM WITH A HOPFIELD-TYPE NEURAL NETWORK
inferred← citeshttps://doi.org/10.25148/etd.fi15101396openalex-snapshot
A hierarchical approach for solving the large-scale traveling salesman problem
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