Title :
Fault-tolerant self-organizing map implemented by wafer-scale integration
Author :
Yasunaga, Moritoshi ; Hachiya, Ippei ; Moki, Keiji ; Kim, Jung Hwan
Author_Institution :
Inst. of Inf. Sci. & Electron., Tsukuba Univ., Ibaraki, Japan
fDate :
6/1/1998 12:00:00 AM
Abstract :
The self-organizing map (SOM) implemented by wafer-scale integration (WSI) will provide significantly high speed and desktop-size hardware for many practical applications such as pattern classification, image-processing, and robotics. Due to the synergistic effect of all neurons for ordering, the SOM-WSI is expected to reach the desired global-ordering state even in the presence of defective neurons. This fault tolerant capability, however, has not yet been studied. In this paper, we propose a fundamental SOM-WSI structure and its defect model. From the defect model, we derive a critical-stuck-output and show that if the defective neuron´s stuck-output is larger than the critical-stuck-output, the defective SOM can eventually organize itself completely tolerating defects. In an ordinary digital design of a neuron, the critical-stuck-output is proved to be small. Therefore, we can expect high-fault tolerance in the SOM-WSI. Experiments are carried out by injecting defective neurons in a neurocomputer currently used as a prototype of the SOM-WSI. The experimental result agrees well with the proposed theory. In addition, we derive an equation to estimate the degree of fault-tolerance in the SOM hardware by expanding the critical-stuck-output calculation. The derived equation can be used to determine the fundamental design parameters in the SOM-WSI as well as other neurocomputer designs.
Keywords :
fault tolerant computing; self-organising feature maps; wafer-scale integration; SOM-WSI; critical-stuck-output; defective neurons; fault-tolerant self-organizing map; fundamental design parameters; global-ordering state; image-processing; neurocomputer design; pattern classification; robotics; synergistic effect; wafer-scale integration; Data mining; Equations; Fault tolerance; Hardware; Image processing; Iterative algorithms; Neurons; Pattern classification; Robots; Wafer scale integration;
Journal_Title :
Very Large Scale Integration (VLSI) Systems, IEEE Transactions on