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The authors have published earlier a parallel & distributed implementation method for the supervised training of feed-forward artificial neural networks using the Harmony Search algorithm. Such implementation was intended to address the training of larger pattern-classification problem. The implementation platforms included both a homogeneous and a(More)
The Harmony Search algorithm is relatively a young stochastic meta-heuristic that was inspired from the improvisation process of musicians. HS has been successfully applied as an optimization method in many scientific and engineering fields and was reported to be competitive alternative to many rivals. In this work a new framework is presented for adapting(More)
—There have been numerous biologically inspired algorithms used to train feed-forward artificial neural networks such as generic algorithms, particle swarm optimization and ant colony optimization. The Harmony Search (HS) algorithm is a stochastic meta-heuristic that is inspired from the improvisation process of musicians. HS is used as an optimization(More)
The authors have published earlier a novel technique for the supervised training of feed-forward artificial neural networks using the Harmony Search algorithm. This paper proposes a parallel and distributed implementation method to speedup the execution time to address the training of larger pattern-classification benchmarking problems. The proposed method(More)
—The hippocampus is a structure in the medial temporal lobe of the brain that is involved in episodic memory function. The texture features of the hippocampus could give better differentiation between Alzheimer's disease and normal controls. The localization of the hippocampus structure in MRI histological images is considered as a multimodal global(More)
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