首页> 外国专利> Self organising neural network formation and evaluation - using e.g. pattern of input and output electrodes, monitoring material changes due to discharge and using in learning process

Self organising neural network formation and evaluation - using e.g. pattern of input and output electrodes, monitoring material changes due to discharge and using in learning process

机译:自组织神经网络的形成和评估-使用例如输入和输出电极的图形,监视由于放电而引起的材料变化并在学习过程中使用

摘要

The method involves placing material under stress by physical or chemical means. Inhomogeneities produced in the material which can be evaluated. The artificial neural network is pref. represented by an electrical discharge through current conductive paths in an insulator (2). It learning process identifies discharges between input electrodes (3) and output electrode (4). The material in the paths changes due to the discharge effect and the output indicates the change which is monitored. A coupled circuit the changes to modify the input in a learning process. ADVANTAGE - Demonstrates neural network learning process.
机译:该方法包括通过物理或化学手段使材料处于应力下。材料中产生的不均匀性可以评估。人工神经网络是首选。表示为通过绝缘子(2)中电流传导路径的放电。学习过程识别输入电极(3)和输出电极(4)之间的放电。路径中的物料会因放电效果而发生变化,并且输出会指示受监控的变化。耦合电路在学习过程中改变改变以修改输入。优势-演示神经网络学习过程。

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