利用訊號連接的想法,重新分析關聯記憶的一種動力函數.原有的記憶訊息為了回覆記憶,採用Hebb的規則形成權值矩陣這些記憶訊息在分類後形成數個網路,而這些網路的結構就決定了動力函數的疊代收斂行為.我們可以知道這個動力函數回覆記憶的極限與限制.最後為了連結網路而產生更強大的網路,我們再增加一個新的記憶訊息來連結它們.

The Content-Addressable Memory Problem is one of the most famous in neural nets. This problem is recently settled by Shih-Tsai. In this thesis, we introduce the notion of the connection and give a different approach to some of results obtained in Shih-Tsai. We shall show that the nets will govern the fixed points base, the transient length, and the behavior of the dynamic equation.

INTRODUCTION.....p1
THE CONNECTION OF DIGITAL SIGNALS.....p4
THE BEHAVIOR OF THE DYNAMIC EQUATION.....p6
CONNECT THE Nets.....p16
REFERENCES.....p18

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