Title | Hardware realization of BSB recall function using memristor crossbar arrays |
Publication Type | Conference Paper |
Year of Publication | 2012 |
Authors | M Hu, H Li, Q Wu, and GS Rose |
Conference Name | Proceedings Design Automation Conference |
Date Published | 07/2012 |
Abstract | The Brain-State-in-a-Box (BSB) model is an auto-associative neural network that has been widely used in optical character recognition and image processing. Traditionally, the BSB model was realized at software level and carried out on high-performance computing clusters. To improve computation efficiency and reduce resources requirement, we propose a hardware realization by utilizing memristor crossbar arrays. In this work, we explore the potential of a memristor crossbar array as an auto-associative memory. More specificly, the recall function of a multi-answer character recognition based on BSB model was realized. The robustness of the proposed BSB circuit was analyzed and evaluated based on massive Monte-Carlo simulations, considering input defects, process variations, and electrical fluctuations. The physical constrains when implementing a neural network with memristor crossbar array have also been discussed. Our results show that the BSB circuit has a high tolerance to random noise. Comparably, the correlations between memristor arrays introduces directional noise and hence dominates the quality of circuits. © 2012 ACM. |
DOI | 10.1145/2228360.2228448 |