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Suboptimum solutions obtained by the Hopfield-Tank neural network algorithm
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What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
inferredcites →https://doi.org/10.1007/3-540-17943-7_119openalex-snapshot
Boltzmann machines and their applications
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Self-Organization and Associative Memory
inferredcites →https://doi.org/10.1007/bf00203001openalex-snapshot
Improving the performance of the Hopfield-Tank neural network through normalization and annealing
inferredcites →https://doi.org/10.1007/bf00320480openalex-snapshot
On the stationary state of Kohonen's self-organizing sensory mapping
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/10.1016/0893-6080(88)90002-0openalex-snapshot
Self-organizing feature maps and the travelling salesman problem
inferredcites →https://doi.org/10.1016/0925-2312(91)90020-copenalex-snapshot
Parallel processing in neural systems and computers
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.79.8.2554openalex-snapshot
Neural networks and physical systems with emergent collective computational abilities.
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/10.1108/ir.1999.04926fae.001openalex-snapshot
Lecture Notes in Computer Science 1205
inferredcites →https://doi.org/10.1109/21.31043openalex-snapshot
Computational-complexity reduction for neural network algorithms
inferredcites →https://doi.org/10.1109/25.69987openalex-snapshot
Channel assignment for cellular radio using neural networks
inferredcites →https://doi.org/10.1109/vetec.1990.110399openalex-snapshot
Practical channel assignment using neural networks
inferredcites →https://doi.org/10.1126/science.220.4598.671openalex-snapshot
Optimization by Simulated Annealing
inferredcites →https://doi.org/10.1287/opre.21.2.498openalex-snapshot
An Effective Heuristic Algorithm for the Traveling-Salesman Problem
inferredcites →https://doi.org/10.7551/mitpress/4931.003.0017openalex-snapshot
*13 Simulated Annealing and Boltzmann Machines
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
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Optimum frequency reuse in mobile telephony systems
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Static and Dynamic Channel Assignment Using Simulated Annealing
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Genetic Algorithms with Stochastic Ranking for Optimal Channel Assignment in Mobile Communications
inferred← citeshttps://doi.org/10.1007/bf00200988openalex-snapshot
Optimization with neural networks: a recipe for improving convergence and solution quality
inferred← citeshttps://doi.org/10.1007/s00422-024-01002-0openalex-snapshot
Beyond the Nobel prizes: towards new synergies between Computational Neuroscience and Artificial Intelligence
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A novel hybrid-maximum neural network in stereo-matching process
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Short time memory problems
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Short time memory problems
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Differential-Algebraic Approach to Linear Programming
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A channel allocation for cellular mobile radio systems using simulated annealing
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Job-shop scheduling using neural networks
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Channel assignment for cellular radio using simulated annealing
inferred← citeshttps://doi.org/10.1109/25.260746openalex-snapshot
Channel assignment in cellular radio networks
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A dynamic channel allocation technique based on Hopfield neural networks
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Sequential packing algorithm for channel assignment under cochannel and adjacent-channel interference constraint
inferred← citeshttps://doi.org/10.1109/25.653070openalex-snapshot
Cellular radio channel assignment using a modified Hopfield network
inferred← citeshttps://doi.org/10.1109/25.806778openalex-snapshot
Transitions from DCA to FCA behavior in a self-organizing cellular radio network
inferred← citeshttps://doi.org/10.1109/49.552073openalex-snapshot
Static and dynamic channel assignment using neural networks
inferred← citeshttps://doi.org/10.1109/5.537110openalex-snapshot
Neural network optimization for multi-target multi-sensor passive tracking
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A neural network for detection of signals in communication
inferred← citeshttps://doi.org/10.1109/82.502314openalex-snapshot
A hardware annealing method for optimal solutions on cellular neural networks
inferred← citeshttps://doi.org/10.1109/glocom.1998.775893openalex-snapshot
A genetic algorithm for the channel assignment problem
inferred← citeshttps://doi.org/10.1109/icnn.1993.298681openalex-snapshot
A neural network model based on differential-algebraic equations for nonlinear programming
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Genetic algorithms for optimal channel assignment in mobile communications
inferred← citeshttps://doi.org/10.1109/pimrc.1997.626990openalex-snapshot
Channel assignment methods in frequency hopping cellular radio networks
inferred← citeshttps://doi.org/10.1109/vetec.1996.501409openalex-snapshot
A mathematical programming approach to the channel assignment problem in radio networks
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Neural Network Applications
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Computer comparison of design knowledge
inferred← citeshttps://doi.org/10.3233/fi-2015-1221openalex-snapshot
Self-Correcting Neural Network for Stereo-matching Problem Solving
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Boundary Pointwise Control for Diffusion Hopfield Neural Network
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