JPRS Report, Science & Technology, China, Fuzzy Logic & Neural Networks.

Abstract

CMOS current mode circuit units are designed and fabricated completing various fuzzy logic operations and relevant processing. Experimental results show that these basic circuits have the advantages of simple structure, high functional density and high speed. They can be used as building blocks to achieve. VLSI implementation of fuzzy hardware. By the use of these circuit units a high speed fuzzy logic microprocessor for a real time hardware expert system has been designed. Back propagation rule has been shown to be an efficient learning algorithm for multilayered neural network. However it is limited because it only finds local minima. Roltzmann machine has also been shown to be an efferent learning rule. But it is limited because it learning rate is too slow. In this paper, we proposed and simulated a quantum learning algorithm for multilayered neural network. It is shown that its learning rate is more rapid than that of Boltzmann machine, and it can find the global minimum unlike back propagation algorithm does.

Open PDF

Document Details

Document Type
Technical Report
Publication Date
Feb 27, 1991
Accession Number
ADA336059

Entities

Organizations

  • Joint Publications Research Service

Tags

Communities of Interest

  • Advanced Electronics
  • C4I
  • Energy and Power Technologies

DTIC Thesaurus Topics

  • Algorithms
  • Artificial Intelligence
  • Circuits
  • Computational Science
  • Computer Science
  • Computers
  • Differential Equations
  • Equations
  • Fuzzy Sets
  • Information Science
  • Logic
  • Logic Gates
  • Neural Networks
  • Probability
  • Self Organizing Systems
  • Simulations
  • Training

Fields of Study

  • Computer science

Readers

  • Adaptive Control and Estimation with Uncertainty in Dynamic Systems.
  • Artificial Intelligence
  • Integrated Circuit Design and Technology.

Technology Areas

  • AI & ML
  • AI & ML - Neural Networks
  • Quantum Computing