Programmable Architectures and Design Methods for Two-Variable Numeric Function Generators

Abstract

This paper proposes programmable architectures and design methods for numeric function generators (NFGs) of two-variable functions. To realize a two-variable function in hardware, we partition a given domain of the function into segments, and approximate the function by a polynomial in each segment. This paper introduces two planar segmentation algorithms that efficiently partition a domain of a two-variable function. This paper also introduces a design method for symmetric two-variable functions (i.e. f(X, Y) = f(Y,X)). This method can reduce the memory size needed for symmetric functions by nearly half with small speed penalty. The proposed architectures allow a systematic design of various two-variable functions. We compare our approach with one based on a one-variable NFG. FPGA implementation results show that, for a complicated function, our NFG achieves 57% of memory size and 60% of delay time of a circuit designed based on a one-variable NFG.

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Document Details

Document Type
Technical Report
Publication Date
Feb 01, 2010
Accession Number
ADA547648

Entities

People

  • Jon T. Butler
  • Shinobu Nagayama
  • Tsutomu Sasao

Organizations

  • Naval Postgraduate School

Tags

Communities of Interest

  • Advanced Electronics

DTIC Thesaurus Topics

  • Accuracy
  • Algorithms
  • Circuits
  • Coefficients
  • Computations
  • Computer Graphics
  • Computer Vision
  • Digital Signal Processing
  • Error Analysis
  • Errors
  • Generators
  • Information Processing
  • Interpolation
  • Logic Gates
  • Probability Distributions
  • Random Variables
  • Signal Processing

Fields of Study

  • Computer science
  • Mathematics

Readers

  • Computer Programming and Software Development.
  • Graph Algorithms and Convex Optimization.