Associative memory network and its hardware design

作者：Xiu, Chunbo^*; Liu, Chang; Cheng, Yi

来源：Neurocomputing, 2015, 158: 204-209.

DOI：10.1016/j.neucom.2015.01.047

• Associative memory
• Hebb rule
• Multi-valued sample pattern
• Strong correlation

In order to improve the performance of the conventional associative memory network, a novel associative memory network composed of input layer, computing layer, associative layer and output layer is proposed. An improved Hebb learning rule is designed for the associative network to perform the associative memory of strong correlation and multi-valued sample patterns. The associative memory can be performed by the associative network in only one forward calculation. The hardware circuit of the network can be designed by simple devices to ensure its parallel computation ability and meet the real-time requirement. Simulation results show that the network has better associative performance than conventional associative network in the binary patterns associative memory, it can store and associate strong correlation sample patterns, and it can retrieve the distortion multi-valued sample patterns with 40% noise correctly.

• 出版日期2015-6-22
• 单位天津工业大学