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Non-algorithmically implemented artificial neural networks and components thereof

机译:非算法实现的人工神经网络及其组件

摘要

Constructing and simulating artificial neural networks and components thereof within a spreadsheet environment results in user friendly neural networks which do not require algorithmic based software in order to train or operate. Such neural networks can be easily cascaded to form complex neural networks and neural network systems, including neural networks capable of self-organizing so as to self-train within a spreadsheet, neural networks which train simultaneously within a spreadsheet, and neural networks capable of autonomously moving, monitoring, analyzing, and altering data within a spreadsheet. Neural networks can also be cascaded together in self training neural network form to achieve a device prototyping system.
机译:在电子表格环境中构造和模拟人工神经网络及其组件将导致用户友好的神经网络,该神经网络不需要基于算法的软件即可进行训练或操作。这样的神经网络可以轻松地级联以形成复杂的神经网络和神经网络系统,包括能够自组织以便在电子表格内进行自我训练的神经网络,在电子表格内同时进行训练的神经网络以及能够自主地进行训练的神经网络。在电子表格中移动,监视,分析和更改数据。神经网络也可以以自训练神经网络的形式级联在一起,以实现设备原型系统。

著录项

  • 公开/公告号AU716593B2

    专利类型

  • 公开/公告日2000-03-02

    原文格式PDF

  • 申请/专利权人 STEPHEN L. THALER;

    申请/专利号AU19970021120

  • 发明设计人 STEPHEN L. THALER;

    申请日1997-01-17

  • 分类号G06F17/00;

  • 国家 AU

  • 入库时间 2022-08-22 01:51:20

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