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threshold neurons
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  “threshold neurons”译为未确定词的双语例句
     From the viewpoint of signal transmission, we studied the SR in summing network constructed by threshold neurons by measuring mutual information and correlation coefficient.
     从信号传输的角度出发,我们用互信息和相关系数等指标研究了加和并行阈值神经元网络中的随机共振现象。
短句来源
     In addition to conventional sub-threshold SR, we also observe the suprathreshold stochastic resonance (SSR) from the results of simulation when many threshold neurons are stimulated with independent noise sources, which means the information transmission and the match between input and output signal match can also be enhanced by the noise even if information-bearing signal is suprathreshold.
     从仿真结果中,除了能观察到传统的阈值下随机共振,还能观察到阈值上随机共振(SSR)现象,也就是说即使输入信号处于阈值上,噪声也能增强信息传递率和输入输出信号的匹配程度。
短句来源
     According to the phenomenon that biological neurons process information by the utilization of noise via stochastic resonance(SR),the output of bipolar random signal and white noise through threshold neurons connected in series or in parallel were studied by Shannon's second theorem. The influence of noise distribution on SR was investigated and the characteristics of the neurons in series were analyzed in terms of goodness and propagation length.
     根据生物神经元是利用噪声通过随机共振机制进行信息处理的现象,以阀值神经元为例,采用香农第二定理,分析了双极性信号和白噪声通过由多个神经元串联或并联组成的系统的输出情况,从品质因数、传输长度等角度对多个神经元串联系统的输出特性随噪声强度变化进行了分析.
短句来源
  相似匹配句对
     The degeneration of neurons was
     实验结果表明:普鲁卡因阻滞对脊髓神经元有明显保护作用。
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     Effects of epidural capsaicin on pain threshold, neurological function and spinal neurons in rabbits
     硬膜外不同浓度辣椒辣素对兔痛阈、神经功能和脊髓神经元结构的影响
短句来源
     Weighted Threshold Model
     加权门限模型
短句来源
     Second, in threshold analyses.
     第二,阈值分析方面。
短句来源
     Relation of Pain Threshold of Tail Flick Reflex and Discharges of Neurons in Nucleus Parafascicularis of Rat Thalamus
     大鼠甩尾痛阈和丘脑束旁核神经元放电的关系
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  threshold neurons
Implementation of multilayer neural network with threshold neurons and its analysis
      
We describe a general diffusion model for analyzing the efficacy of individual synaptic inputs to threshold neurons.
      
A general diffusion model for analyzing the efficacy of synaptic input to threshold neurons
      
However, some low-threshold neurons started to react to noxious mechanical stimulation and some high-threshold neurons started to respond to innocuous brushing after lidocaine injection.
      
The wide dynamic range and inhibitory low threshold neurons were located primarily in the caudal third of VPM, while the excitatory low threshold neurons were located throughout.
      
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On the basis of discussing dineral Feed-FOrward Network(GFFN), a Sequential Learng Ahead Masking Medel and its relevant algorithm for pattern classification are proud. By adapting this model to the pattern clssifier, the computer simulation results show that not only the convergence sped and performance of the network are much better than the existing modified BP algorithms, but also the required network scale is reduced greatly. Moreover, Double-Threshold Neuron(DTN) has been applied to SLAM network for...

On the basis of discussing dineral Feed-FOrward Network(GFFN), a Sequential Learng Ahead Masking Medel and its relevant algorithm for pattern classification are proud. By adapting this model to the pattern clssifier, the computer simulation results show that not only the convergence sped and performance of the network are much better than the existing modified BP algorithms, but also the required network scale is reduced greatly. Moreover, Double-Threshold Neuron(DTN) has been applied to SLAM network for pattern classification and the SLAM pattern classifier shows potential of continuously growing and improving. At last, the SLAM pattern classifier has been implemented on the CASSANDRA-I micro-neurocomputer and the results are provided.

本文讨论了不分层的通用前馈网络(GFFN),并提出了一种作为模式分类器的排序学习前向掩蔽(SLAM)模型及其算法实验结果表明,这种网络作为模式分类器用时,学习时间远小于各种改进的BP网络而且所需使用的神经元数量也有显著的减少本文还介绍了这种SLAM模型在应用双阈值神经元DTN时进一步减少神经元数量的实验结果及其网络结构和学习算法,以及这种模型的模式分类器所具有的不断扩展与改善的能力论文还介绍了SLAM模型模式分类器在CASSANDRA-I小型神经计算机上实现的实验结果:在256维输入空间1024个随机样本的分类情况,学习时间约3小时20分,判别时间为0.007秒.

According to the phenomenon that biological neurons process information by the utilization of noise via stochastic resonance(SR),the output of bipolar random signal and white noise through threshold neurons connected in series or in parallel were studied by Shannon's second theorem.The influence of noise distribution on SR was investigated and the characteristics of the neurons in series were analyzed in terms of goodness and propagation length.The results demonstrate the optimal noise-assisted information...

According to the phenomenon that biological neurons process information by the utilization of noise via stochastic resonance(SR),the output of bipolar random signal and white noise through threshold neurons connected in series or in parallel were studied by Shannon's second theorem.The influence of noise distribution on SR was investigated and the characteristics of the neurons in series were analyzed in terms of goodness and propagation length.The results demonstrate the optimal noise-assisted information transmission due to SR.To the neural network in series,information transmission decreases as the levels increase,but it is quite the contrary to the parallel case.The noise variance only affects the intensity of SR,no matter with the SR phenomenon.Compared with Gaussian noise,the even white noise has stronger SR behavior.All these proved the noise was effective in signal transmission.

根据生物神经元是利用噪声通过随机共振机制进行信息处理的现象,以阀值神经元为例,采用香农第二定理,分析了双极性信号和白噪声通过由多个神经元串联或并联组成的系统的输出情况,从品质因数、传输长度等角度对多个神经元串联系统的输出特性随噪声强度变化进行了分析.实验结果表明:系统存在随机共振现象,即存在最优的噪声量可以最大限度地增强信息传输;串联时传输信息量随级数的增大而减小,并联时正好相反;噪声的分布形式只影响共振效应的强弱,而不影响系统的随机共振特性;均匀白噪声比高斯白噪声有更强的共振效应.从而说明了噪声对信息传输的积极作用.

 
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