A HYBRID ANALOG-DIGITAL DIFFERENTIAL ANALYZER SYSTEM,

Abstract

A true hybrid (parallel analog-digital) differential analyzer, by combining many of the advantages of both analog and digital systems, may be useful in applications where moderately high-accuracy real-time and faster-than-real-time computing is required. This thesis covers the results of theoretical and experimental studies of a hybrid computing system. A hybrid system gains accuracy through the use of digital techniques; analog (continuous) interpolation frees the hybrid system of truncation and round-off errors. The system also preserves most of the ease-of-programming features associated with analog computers. These features permit a hybrid differential analyzer, using only a few digital bits and a moderate digital clock rate, to achieve both an accuracy and a bandwidth or speed-of-operation comparable to modern high-speed digital differential analyzers. The system is similar to the one originally proposed by H. Skramstad in 1959, but differs in at least two respects. First, integrator interpolations are performed by using a sawtooth waveform generator (as suggested by H. Schmid in 1961). Second, the analog computing operations are periodically held for a controlled time interval, while digital updating and carry generation operations are performed. Thus, the hybrid system may be regarded as a relatively inexpensive incremental parallel DDA whose truncation and round-off errors are essentially eliminated through interpolation with repetitive analog computing elements.

Document Details

Document Type
Technical Report
Publication Date
Jun 01, 1963
Accession Number
AD0479647

Entities

People

  • John V. Wait

Organizations

  • University of Arizona

Tags

DTIC Thesaurus Topics

  • Accuracy
  • Analog Computers
  • Analyzers
  • Computer Programming
  • Computers
  • Differential Analyzers
  • Errors
  • Generators
  • Hybrid Systems
  • Interpolation
  • Sawtooth Waveforms
  • Time Intervals
  • Truncation
  • Waveform Generators
  • Waveforms

Readers

  • Computer Engineering
  • Computer Science/Computer Engineering/Data Science/Digital Signal Processing.
  • Finite Element Method (FEM) for solving Partial Differential Equations (PDEs)