GRAPHICAL DATA PROCESSING RESEARCH STUDY AND EXPERIMENTAL INVESTIGATION.

Abstract

A small experimental learning MINOS I was developed in order to evaluate the feasibility of this type of machine for categorizing graphical data from maps, charts and aerial photographs. A much larger machine, MINOS II, has recently been constructed, including an optical preprocessor which provides a good match between the raw data and thelearning machine. Three rationales governing the design of masks for the preprocessor are discussed; the preprocessor is seen as performing operations special to the problem being considered, whereas the learning machine is a general categorizer. Learning machines make use of a component not in common use, a device to store an analog number, which may be read-out nondestructively as an analog level. Several types of magnetic 'weight' have been investigated. MINOS II uses a magnetic weight with second-harmonic read-out. Competitive weights use multiaperture magnetic cores, and magnetostrictive delay lines. The learning machine contains two layers of threshold logic. The first layer contains 66 association-units wire 100 input lines; there are 6732 weights in the first layer-the extras are for threshold levels. Training is by 'majority-rule' logic, implemented automatically; input signals may be either (1,-1), (1,0), or (1,0,-1). The output code may be either 6 or 9 bits, with arbitrary selection of categories. (Author)

Document Details

Document Type
Technical Report
Publication Date
Jun 01, 1963
Accession Number
AD0460517

Entities

People

  • A. E. Brain

Organizations

  • SRI International

Tags

DTIC Thesaurus Topics

  • Aerial Photographs
  • Data Processing
  • Delay Lines
  • Education
  • Learning
  • Learning Machines
  • Magnetic Cores
  • Photographic Materials
  • Photographs
  • Photography
  • Teaching Methods
  • Training

Readers

  • Computer Programming and Software Development.
  • Neural Network Machine Learning.