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Building Electronic ML Neuron Networks and Its Analysis

Author: XueLiang
Tutor: WangJiang
School: Tianjin University
Course: Detection Technology and Automation
Keywords: Electronic neurons Network Branch Chemical synapses CPG
CLC: TP399-C8
Type: Master's thesis
Year: 2008
Downloads: 65
Quote: 0
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Abstract


A large number of neurons in the nervous system , neurons in the neural basis of scientific research . Neurons characteristic of biological experiments , costly , and difficult to achieve . Mathematical simulation analysis of neuronal networks , computing speed has become the biggest bottleneck . In recent years , the nerves the morphology gradually rise by more and more attention from scholars . Nerve morphology refers to the dynamic characteristics of the electronic circuit of biological neurons . The electronic neurons can provide a real time scale , rapid experimental platform , in neuron network characteristics , bionics research , as well as treatment of neurological diseases and other aspects of great significance . ML analysis of mathematical models based on realized ML simulated neurons and bifurcation characteristic analysis . Bursting oscillator is achieved through the introduction of the method of slowly varying current and slowly varying current parameters of the impact of the bursting characteristics . Chemical synaptic connection is the most important in the nervous system , and plays an important role in the generation and conduction of nerve messages . Inhibitory and excitatory chemical synapse circuit model . Synchronization rhythm , and a detailed analysis of the the mutual to inhibit neurons competition discharge behavior , analysis of the impact of external stimuli current system characteristics . ML neurons of the electronic , the establishment of several neuronal networks , comprising the inhibitory or excitatory network , to conduct a detailed analysis . The central pattern generator (CPG) is composed of a few to several tens of function can be identified in the middle of neurons private network, and generating a rhythmic neural output . Established network can be composed of a variety of CPG . Lobster pyloric rhythm generator is a simple CPG, their normal work action potential , and a simple analysis of the characteristics of its phase remains . Finally, using the network formed by the control of the motor can be described by simple animal movements . The results of this study can be directly extended to large - scale neuronal networks , research conduction of action potentials and the role of law .

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