1 November 1992 Implementing associative memories on nonideal analog systems
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Proceedings Volume 1826, Intelligent Robots and Computer Vision XI: Biological, Neural Net, and 3D Methods; (1992) https://doi.org/10.1117/12.131589
Event: Applications in Optical Science and Engineering, 1992, Boston, MA, United States
Abstract
We consider the implementation of high capacity Ho-Kashyap (HK) associative processors (APs) on non-ideal optical and analog VLSI systems. Processor non-idealities considered include quantization, non-uniform beam illumination, and nonlinear device characteristics. New training-out techniques to overcome these non-idealities are advanced. We obtain optimal performance in the presence of stochastic noise by proper selection of the processor parameter (sigma) syn. We derive important results that allow us to a priori determine the optimal value of (sigma) syn and the expected recall accuracy P'c without having to simulate the specific processor. We present a new algorithm that allows us to achieve storage near the theoretical maximum capacity (2 N, where N is the dimensionality of the input vector) with excellent recall accuracy. Optical laboratory results are included. We achieved storage of 1.5 N with recall accuracy P'c >= 95% with input noise of standard deviation (sigma) 1 equals 0.02 present and with optical analog components with 5 bit input accuracy and 8 bit memory matrix accuracy. With higher accuracy analog VLSI components (10 bit input accuracy and 11 bit weight accuracy), we achieve storage of 1.75 N with P'c equals 96.43%.
© (1992) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Leonard Neiberg, David P. Casasent, "Implementing associative memories on nonideal analog systems", Proc. SPIE 1826, Intelligent Robots and Computer Vision XI: Biological, Neural Net, and 3D Methods, (1 November 1992); doi: 10.1117/12.131589; https://doi.org/10.1117/12.131589
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