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SIMULATION OF INTELLIGENT COMPUTATIONAL MODELS IN BIOLOGICAL SYSTEMS

机译:生物系统中智能计算模型的仿真

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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.
机译:人的大脑可以使用具有大量神经元的神经网络执行一系列复杂的计算和逻辑推理。自从Hodgkin和Huxley提出了一系列方程式来描述尖峰神经元的电生理特性以来,已经开发了各种神经元网络结构。通过现在可以通过电子电路或计算机程序进行模拟的神经科学研究。本文基于与突触的尖峰时间相关的可塑性有关的生物学特性,模拟了一种自适应学习机制。开发该机制的特定接受域以识别模式。此机制可用于解释生物系统中的某些适应性行为,也可应用于人工智能系统。

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