Title :
Simulation of Intelligent Computational Models in Biological Systems
Author :
Wu, Qing-Xiang ; McGinnity, Martin ; Maguire, Liam ; Belatreche, Ammar ; Glackin, Brendan
Author_Institution :
Univ. of Ulster at Magee, Derry
Abstract :
The human brain can perform a range of complicated computations and logical reasoning using neural networks with a huge number of neurons. Since Hodgkin and Huxley proposed a set of equations to describe the electrophysiological properties of spiking neurons, various network structures of neurons have been developed through neuroscience research that can now be simulated by electronic circuits or computer programs. In this paper, an adaptive learning mechanism is simulated based on the biological property related to the spike time dependent plasticity of synapses. A demonstration shows that such spiking neurons are able to develop their specific receptive field for recognition of patterns. This mechanism can be used to explain some adaptive behaviours in biological systems. It is can also be applied to artificial intelligent systems.
Keywords :
adaptive systems; biology computing; learning (artificial intelligence); learning systems; neural nets; adaptive learning mechanism; artificial intelligent system; biological system; human brain; intelligent computational model; pattern recognition; receptive field; spike time dependent plasticity; spiking neurons; synapses; Biological system modeling; Biological systems; Biology computing; Brain modeling; Circuit simulation; Computational intelligence; Computational modeling; Computer networks; Humans; Neurons; Adaptive learning; Computational model; Spiking neural network; Spiking time dependent plasticity;
Conference_Titel :
Machine Learning and Cybernetics, 2007 International Conference on
Conference_Location :
Hong Kong
Print_ISBN :
978-1-4244-0973-0
Electronic_ISBN :
978-1-4244-0973-0
DOI :
10.1109/ICMLC.2007.4370470
