Hybrid Pipeline Structure for Self-Organizing Learning Array

In recent years, many efforts have been put in applying the concept of reconfigurable computing to neural networks. In our previous pursuits, an innovative self-organizing learning array (SOLAR) was developed. However, traditional multiplexer method to achieve reconfigurable connection has its limit for larger networks. In this paper, we propose a novel pipeline structure, which offers flexible, possibly large number of dynamically configurable connections and which utilizes each node’s computing ability. The hardware re-sources demand of the proposed structure is a linear function of the network size, which is especially useful for building a large network that can handle complicated real-world applications.

• Type: Conference
• Year: 2007
• Where: ISNN
• Authors: Janusz A. Starzyk, Mingwei Ding, Yinyin Liu
• Keywords: ISNN 2007, Reconfigurable Computing, Self-organizing Learning Array, Traditional Multiplexer Method