Improved exploration in Hopfield network state-space through parameter perturbation driven by simulated annealing

Article Abstract:

An approach called local minima escape simulated annealing (LMESA) was formulated to address the discrete optimization problems of the Hopfield neural network. The approach, which acts as a modified version of local minima escape (LME) algorithm, utilizes perturbation mechanism and simulated annealing strategy. Implementation of the approach on Weighted Maximum Independent Set problem showed its effectiveness in producing solutions that are much effective than those obtained using the traditional LME approach.

Research and Development in the Physical, Engineering, and Life Sciences, Mathematics, Simulated annealing (Mathematics)

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Response surface methodology: a neural network approach

Article Abstract:

Neural networks have been found to be applicable in generating response surface methodology. The two-stage approach to generating the best parameters for an unknown model first involves neural networks being trained to identify an unknown function and then to identify the derivatives of this function generated by the first neural network. The neural networks are then iteratively used to compute parameters that optimize the function.

Operations Research, Usage, Simulation methods, Simulation, Response surfaces (Statistics)

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Neural networks for image and video compression: a review

Article Abstract:

An assessment was undertaken with regards to works conducted on the field of neural networks and compression. The assessment specifically deals with methods in which neural networks can be utilized to improve still image and video compression. The evolution of stand-alone techniques, one of the neural network techniques implemented in compression, that vary from simple to efficient compression techniques was also noted.

Operations research, Management science, Analysis, Data compression

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