Titlebook: Competitively Inhibited Neural Networks for Adaptive Parameter Estimation; Michael Lemmon Book 1991 Springer Science+Business Media New Yo

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书目名称Competitively Inhibited Neural Networks for Adaptive Parameter Estimation影响因子(影响力)




书目名称Competitively Inhibited Neural Networks for Adaptive Parameter Estimation影响因子(影响力)学科排名




书目名称Competitively Inhibited Neural Networks for Adaptive Parameter Estimation网络公开度




书目名称Competitively Inhibited Neural Networks for Adaptive Parameter Estimation网络公开度学科排名




书目名称Competitively Inhibited Neural Networks for Adaptive Parameter Estimation被引频次




书目名称Competitively Inhibited Neural Networks for Adaptive Parameter Estimation被引频次学科排名




书目名称Competitively Inhibited Neural Networks for Adaptive Parameter Estimation年度引用




书目名称Competitively Inhibited Neural Networks for Adaptive Parameter Estimation年度引用学科排名




书目名称Competitively Inhibited Neural Networks for Adaptive Parameter Estimation读者反馈




书目名称Competitively Inhibited Neural Networks for Adaptive Parameter Estimation读者反馈学科排名

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慢跑

The CINN Algorithm,ity and steady states of the system. These theorems provide a parametric characterization of the CINN’s steady states. The characterization allows us to predict the network’s STM and LTM states given the input vector. We can fashion these results into an algorithm which we call the CINN Algorithm. T

Veneer

CINN Learning,ian product of the LTM space and time axis (also called (w, t)-space) along which the neural density is constant. They provide a convenient way of studying the continuum model’s solutions. This section derives the characteristic trajectories for the continuum model. It will be shown that under certa

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来就得意

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Capitulate

https://doi.org/10.1007/978-3-642-99333-6 other neurons in the network. The following sections formally introduce the CINN state equations and compare them to existing neural network models such as the adaptive resonance theory (ART) network [18] [3] and Kohonen’s self-organizing feature map [27] (sometimes called the adaptive vector quantization or AVQ algorithm).

失误

The CINN Equations, other neurons in the network. The following sections formally introduce the CINN state equations and compare them to existing neural network models such as the adaptive resonance theory (ART) network [18] [3] and Kohonen’s self-organizing feature map [27] (sometimes called the adaptive vector quantization or AVQ algorithm).