Stand-Alone Hardware-Based Learning System

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概要

• 論文の詳細を見る

• The probabilistic Random Access Memory (pRAM) is a biologically-inspired model of a neuron. The pRAM behaviour is described in this paper in relation to binary and real-valued input vectors. The pRAM is hardware-realisable, as is its reinforcement training algorithm. The pRAM model may be applied to a wide range of artificial neural network applications, many of which are classification tasks. The application presented here is a control problem where an inverted pendulum, mounted on a cart, is to be balanced. The solution to this problem using the pRAM-256, a VLSI pRAM controller, is shown.

• 社団法人応用物理学会の論文
• 1995-02-28

著者

• Ng Chi

  Department Of Electronic Engineering City Polytechnic Of Hong Kong

• Clarkson Trevor

  Department Of Electronic And Electrical Engineering King's College

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