New High-Order Associative Memory System Based on Newton's Forward Interpolation

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概要

• 論文の詳細を見る

• A double-layer Associative Memory System (AMS) based on the Cerebella Model Articulation Controller (CMAC) (CMAC-AMS), owing to its advantages of simple structures. fast searching procedures and strong mapping capability between multidimensional input/output vectors, has been successfully used in such applications as real-time intelligent control, signal processing and pattern recognition. However, it is still suffering from its requirement for a large memory size and relatively low precision. Furthermore, the hash code used in its addressing mechanism for memory size reduction can cause a data-collision problem. In this paper, a new high-order Associative Memory System based on the Newton's forward interpolation formura (NFI-AMS) is proposed. The NFI-AMS is capable of implementing high-precision approximation to multivariable functions with arbitrarily given sampling data. A learning algorithm and a convergence theorem of the NFI-AMS are proposed. The network structure and the scheme of its learning algorithm reveal that the NFI-AMS has advantages over the conventional CMAC-type AMS in terms of high precision of learning, much less required memory size without the data-collision problem, and also has advantages over the multilayer Back Propagation (BP) neural networks in terms of much less computational effort for learning and fast convergence rate. Numerical simulations verify these advantages. The proposed NFI-AMS, therefore, has potential in many application areas as a new kind of associative memory system.

• 社団法人電子情報通信学会の論文
• 1998-12-25

著者

• Hama Hiromitsu

  The Department Of Information And Communication Engineering Faculty Of Engineering Osaka City Univer

• Liu Zhongkan

  the Department of Applied Mathematics, Beijing University of Aeronautics and Astonautics

• Liu Zhongkan

  The Department Of Applied Mathematics Beijing University Of Aeronautics And Astronautics

• Liu Zhongkan

  The Department Of Applied Mathematics Beijing University Of Aeronautics And Astonautics

• XING Chunfeng

  the Beijing Union University

関連論文

• Spatial Array Processing of Wide Band Signals with Computation Reduction
• New High-Order Associative Memory System Based on Newton's Forward Interpolation

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