Associative Gray Level Pattern Processing using Binary Decomposition and b1; b2; Memories

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• 作者：Humberto Sossa ; Ricardo Barr¨®n ; Francisco Cuevas and Carlos Aguilar
• 关键词：associative memories ; b1 ; b2 ; object recognition ; pattern recognition
• 刊名：Neural Processing Letters
• 出版年：2005
• 出版时间：August 2005
• 年：2005
• 卷：22
• 期：1
• 页码：85-111
• 全文大小：584 KB

文摘

In this note we show how a binary memory can be used to recall gray-level patterns. We take as example the b1; b2; associative memories recently proposed in Yáñez, Associative Memories based on order Relations and Binary Operators(In Spanish), PhD Thesis, Center for computing Research, February of 2002, only useful in the binary case. Basically, the idea consists on that given a set of gray-level patterns to be first memorized: (1) Decompose them into their corresponding binary patterns, and (2) Build the corresponding binary associative memory (one memory for each binary layer) with each training pattern set (by layers). A given pattern or a distorted version of it, it is recalled in three steps: (1) Decomposition of the pattern by layers into its binary patterns, (2) Recalling of each one of its binary components, layer by layer also, and (3) Reconstruction of the pattern from the binary patterns already recalled in step 2. The proposed methodology operates at two phases: training and recalling. Conditions for perfect recall of a pattern either from the fundamental set or from a distorted version of one them are also given. Experiments where the efficiency of the proposal is tested are also given.