A Primer on Polynomial Resultants

Abstract

Nonlinearity is one of the most stubborn difficulties of contemporary engineering and science. In this paper we are concerned with a broadly useful tool, the resultant, for manipulating polynomial nonlinearities, and we review several techniques for solving systems of nonlinear polynomial equations. The resultant, a classical algebraic tool, has become much more practical recently with the advent of symbolic software (such as Mathematics and Maple) which can evaluate 10x10 symbolic determinants in a matter of minutes on a desktop computer. While much of this paper is concerned with applying resultants to systems of univariate equations, the last section considers the generalization to the multivariate situation. Nonlinear multivariate applications appear in various areas of engineering such as chaos, signal processing, circuit theory, robotics and control theory. Two illustrations of the power of the resultant formalism are provided. First, the problem of finding the coordinates on the Earth's surface viewed by each pixel of a reconnaissance aircraft camera is discussed. Second, the Lorenz model of chaos theory if considered.

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Document Details

Document Type
Technical Report
Publication Date
Dec 05, 1991
Accession Number
ADA246883

Entities

People

  • Robert M. Williams
  • Ronald F. Gleeson

Organizations

  • Naval Air Warfare Center Warminster

Tags

Communities of Interest

  • Air Platforms
  • C4I
  • Energy and Power Technologies
  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Aircrafts
  • Algebra
  • Algebraic Geometry
  • Computer Programming
  • Computers
  • Coordinate Systems
  • Engineering
  • Equations
  • Line Of Sight
  • Mathematics
  • Military Research
  • Numbers
  • Polynomials
  • Quadratic Equations
  • Reconnaissance
  • Reconnaissance Aircraft
  • Signal Processing

Fields of Study

  • Mathematics

Readers

  • Calculus or Mathematical Analysis
  • Theoretical Analysis.
  • Wave Propagation and Nonlinear Chaotic Dynamics.

Technology Areas

  • AI & ML
  • AI & ML - Machine Learning Algorithms
  • Autonomy