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標題: 多元雙向聯想記憶類神經網路之探討
作者: 冷明河
關鍵字: 類神經網路;雙向聯想記憶網路;多元雙向聯想記憶網路;鬆弛法
出版社: 國立中興大學工學院;Airiti Press Inc.
Project: 興大工程學報, Volume 10, Issue 1, Page(s) 59-82.
The Multi-BAM associative neural network is proposed in this paper, which is an extension of the Bidirectional Associative Memory (BAM). Instead of only two units, as in the BAM, the Multi-BAM consists of many units. It operates in an iterative way like that of the relaxation process. The energy of the network is also defined, and is proven to converge during the iterative process of the network. Based on the property that the energy of the network will reach its local minimum when all the units in the network are correct, we have derived the sufficient conditions that the network must meet in order that the network, when errors exist in its units, will be able to reach the correct recalls during iteration. Some experimental simulations have been done to investigate the network's performance under various error conditions. These experiments have also compared the effects of the network sizes and positions of the erroneous units in the network on the network performance.

ISSN: 1017-4397
Appears in Collections:第10卷 第1期

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