A new evolutionary approach for neural spike detection based on genetic algorithm

•Independently adaptive neural spike detection implementing genetic algorithm.•Improved spike detection offers lower transmission power consumption.•Potential for self-programming hardware implementation. Identification of the epileptic features in nervous signals is one of the main goals of neurosc...

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Veröffentlicht in:	Expert systems with applications Jg. 42; H. 1; S. 462 - 467
Hauptverfasser:	Zarifia, Mohammad Hossein, Ghalehjogh, Negar Karimi, Baradaran-nia, Mehdi
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Amsterdam Elsevier Ltd 01.01.2015 Elsevier
Schlagworte:	Applied sciences Background noise Biological and medical sciences Central nervous system Computer science; control theory; systems Computer simulation Computer systems and distributed systems. User interface Data processing. List processing. Character string processing Electrophysiology Evolutionary Exact sciences and technology Fundamental and applied biological sciences. Psychology Genetic algorithm Genetic algorithms Headache. Facial pains. Syncopes. Epilepsia. Intracranial hypertension. Brain oedema. Cerebral palsy Manuals Medical sciences Memory organisation. Data processing NEO Nervous system (semeiology, syndromes) Neural spike detection Neurology Neuronal signal Patients Recording Software Spikes Vertebrates: nervous system and sense organs Neuronal signal NEO Neural spike detection Genetic algorithm Current information Energy consumption Tracking Evolutionary algorithm Epilepsy Expert system Central nervous system Bandwidth Selection criterion Localization Neurological disorder Biomedical engineering Threshold Spike Implant Health Neural network Real time Filter Power device Tracking(movable target) Signal processing Field potential Wireless network Signal to noise ratio
ISSN:	0957-4174, 1873-6793
Online-Zugang:	Volltext
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