脑神经网络

脑神经网络脑神经网络
  1. 脑神经网络综合康复平台的研究

    Study on the Integrated Rehabilitation Platform for Cerebral Nerve Net

  2. 通常时滞使系统的稳定性变得非常复杂,因此,研究时滞脑神经网络的稳定性是非常必要的。

    Therefore , it is very necessary that we study the stability of neural network with delays .

  3. 本文对一类脑神经网络模型的同步状态进行了稳定性和定性分析。

    In this paper , we analyze the stability and qualitative properties of the synchronized model of brain neural network .

  4. 结论采取双手交替运动模式,fMRI不仅显示了受累侧运动区的变形与移位,而且揭示了一种新的功能重组模式,即运动功能重组可能涉及分布于全脑的整个神经网络。

    Conclusion With an alternating hand movement task , the present fMRI study not only demonstrated the displacement and distortion of the M1 in the tumor affected hemisphere , but also revealed a new pattern of functional reorganization , which appears to involve a distributed network throughout the whole brain .

  5. 脑电信号神经网络智能分析系统的研制

    Research on intelligent analytical system of cerebral potential signals ' diagnosis

  6. 他本人在实际研究中选择视觉意识作为突破口,并重视脑损伤和神经网络的研究。

    He himself chooses visual consciousness as a breakthrough in the practical studies and prizes the studies of brain damages and neural networks .

  7. 在现代信息科学和生命科学相互交叉渗透的研究领域,由生物免疫系统启发的人工免疫系统(AIS)是继脑神经系统(神经网络)和遗传系统(进化计算)之后的又一个研究热点。

    Crossing the penetrating research region with life science mut ua lly at modern information science , artificial immune system ( AIS ) that inspired by biological immune system is a hot point after brain nervous system ( nerual n etwork ) and genetic system ( evolve calculation ) .

  8. 材料不同及编码或提取水平不同,所涉及脑功能区及神经网络机制可能有差异。

    With the variation of materials and levels of encoding / retrieval , there existed differences in mechanisms of neural network ( NN ) and the related functional regions of brain .

  9. NO的发现为脑科学和人工神经网络以及神经信号处理领域许多传统的观点提供了一个新的启示。在现有的自组织神经网络模型中引入NO机制是一个有价值的研究方向。

    NO provides some new inspiration about some of the traditional tenets in the domain of brain science , artificial neural network and neural signal processing , and it is valuable to introduce NO mechanism into self-organizing neural network models .