Artificial neural circuit net for executing self-organization by learning input information
专利汇可以提供Artificial neural circuit net for executing self-organization by learning input information专利检索，专利查询，专利分析的服务。并且PURPOSE: To quickly obtain a real solution or an effective approximate solution for combination optimization having high complexity by providing the neural circuit net with mutual connection and a phase capable of resolving also a combination optimization problem and executing self-organization allowing the mixture of sequential updating and batch updating.
CONSTITUTION: The neural circuit net capable of executing self-organization is constituted of a schedular 1, input data 2, an input layer 3, a switch 4 for a sequential updating type and a batch updating type, an updating calculating mechanism 5 for updating the state of an artificial neural cell, an artificial neural circuit net 6 to be self-organized, and information routes 7 to 10 to the schedular 1. When necessary, a different property state can be separated as a direct product, the mixture of sequential updating and batch updating can be executed, the mutual connection and phase between the artificial neural cells can be obtained and various cost functions can be processed. Consequently, a real solution or an effective approximate solution for a combination optimization problem which may be extremely difficult for a serial processing computer can quickly be obtained.
COPYRIGHT: (C)1991,JPO&Japio，下面是Artificial neural circuit net for executing self-organization by learning input information专利的具体信息内容。
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