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基于抑制性突触可塑性的反馈神经回路兴奋性与抑制性动态平衡 被引量:11
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作者 王美丽 王俊松 《物理学报》 SCIE EI CAS CSCD 北大核心 2015年第10期416-423,共8页
大脑皮层的兴奋性与抑制性平衡是维持正常脑功能的前提,而其失衡会诱发癫痫、帕金森、抑郁症等多种神经疾病,因此兴奋性与抑制性平衡的研究是脑科学领域的核心科学问题.反馈神经回路是脑皮层网络的典型连接模式,抑制性突触可塑性在兴奋... 大脑皮层的兴奋性与抑制性平衡是维持正常脑功能的前提,而其失衡会诱发癫痫、帕金森、抑郁症等多种神经疾病,因此兴奋性与抑制性平衡的研究是脑科学领域的核心科学问题.反馈神经回路是脑皮层网络的典型连接模式,抑制性突触可塑性在兴奋性与抑制性平衡中扮演关键角色.本文首先构建具有抑制性突触可塑性的反馈神经回路模型;然后通过计算模拟研究揭示在抑制性突触可塑性的调控下反馈神经回路的兴奋性与抑制性可取得较高程度的动态平衡,并且二者的平衡对输入扰动具有较强的鲁棒性;其次给出了基于抑制性突触可塑性的反馈神经回路兴奋性与抑制性平衡机理的解释;最后发现反馈回路神经元数目有利于提高兴奋性与抑制性平衡的程度,这在一定程度上解释了为何神经元之间会存在较多的连接.本文的研究对于理解脑皮层的兴奋性与抑制性动态平衡机理具有重要的参考价值. 展开更多
关键词 抑制性突触可塑性 反馈神经回路 兴奋性抑制性平衡 leaky integrate—and—fire神经
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Hybrid control based on inverse Prandtl-Ishlinskii model for magnetic shape memory alloy actuator 被引量:2
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作者 周淼磊 高巍 田彦涛 《Journal of Central South University》 SCIE EI CAS 2013年第5期1214-1220,共7页
The hysteresis characteristic is the major deficiency in the positioning control of magnetic shape memory alloy actuator. A Prandtl-Ishlinskii model was developed to characterize the hysteresis of magnetic shape memor... The hysteresis characteristic is the major deficiency in the positioning control of magnetic shape memory alloy actuator. A Prandtl-Ishlinskii model was developed to characterize the hysteresis of magnetic shape memory alloy actuator. Based on the proposed Prandtl-Ishlinskii model, the inverse Prandtl-Ishlinskii model was established as a feedforward controller to compensate the hysteresis of the magnetic shape memory alloy actuator. For further improving of the positioning precision of the magnetic shape memory alloy actuator, a hybrid control method with hysteresis nonlinear model in feedforward loop was proposed. The control method is separated into two parts: a feedforward loop with inverse Prandtl-Ishlinskii model and a feedback loop with neural network controller. To validate the validity of the proposed control method, a series of simulations and experiments were researched. The simulation and experimental results demonstrate that the maximum error rate of open loop controller based on inverse PI model is 1.72%, the maximum error rate of the hybrid controller based on inverse PI model is 1.37%. 展开更多
关键词 magnetic shape memory alloy HYSTERESIS hybrid control Prandtl-Ishlinskii model neural network
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