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Simulation of Intelligent Computational Models in Biological Systems

Biomedical Sciences Research Institute Computer Science Research Institute Environmental Sciences Research Institute Nanotechnology & Advanced Materials Research Institute

Wu, Qingxiang, McGinnity, TM, Maguire, LP, Belatreche, Ammar and Glackin, Brendan (2007) Simulation of Intelligent Computational Models in Biological Systems. In: The International Conference on Machine Learning and Cybernetics (ICMLC2007). IEEE. 5 pp. [Conference contribution]

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URL: http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=4370470&tag=1

DOI: 10.1109/ICMLC.2007.4370470


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 electro- physiological 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.

Item Type:Conference contribution (Lecture)
Keywords:Spiking neural network; computational model; adaptive learning; spiking time dependent plasticity
Faculties and Schools:Faculty of Computing & Engineering
Faculty of Computing & Engineering > School of Computing and Intelligent Systems
Research Institutes and Groups:Computer Science Research Institute
Computer Science Research Institute > Intelligent Systems Research Centre
ID Code:20652
Deposited By:Dr Qingxiang Wu
Deposited On:17 Jan 2012 15:00
Last Modified:17 Jan 2012 15:00

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