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.
|Title of host publication||Unknown Host Publication|
|Number of pages||5|
|Publication status||Published (in print/issue) - 1 Aug 2007|
|Event||The International Conference on Machine Learning and Cybernetics (ICMLC2007) - |
Duration: 1 Aug 2007 → …
|Conference||The International Conference on Machine Learning and Cybernetics (ICMLC2007)|
|Period||1/08/07 → …|
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- Spiking neural network
- computational model
- adaptive learning
- spiking time dependent plasticity