Design and Implementation of RNS-Based Adaptive Filters

  • Javier Ramírez
  • Uwe Meyer-Bäse
  • Antonio García
  • Antonio Lloris
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2778)

Abstract

This paper presents the residue number system (RNS) implementation of reduced complexity and high performance adaptive FIR filters on Altera APEX20K field-programmable logic (FPL) devices. Index arithmetic over Galois fields along with a selection of a small wordwidth modulus set are keys for attaining low-complexity and high-throughput. The replacement of a classical modulo adder tree by a binary adder with extended precision followed by a single modulo reduction stage improved area requirements by 10% for a 32-tap FIR filter. A block LMS (BLMS) implementation was preferred for the update of the adaptive FIR filter coefficients. RNS-FPL merged filters demonstrated its superiority when compared to 2C (two’s complement) filters, being about 65% faster and requiring fewer logic elements for most study cases.

Keywords

Residue Number System VLSI Signal Processing Galois Field Move Target Detection Binary Adder 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2003

Authors and Affiliations

  • Javier Ramírez
    • 1
  • Uwe Meyer-Bäse
    • 2
  • Antonio García
    • 1
  • Antonio Lloris
    • 1
  1. 1.Department of Electronics and Computer TechnologyUniversity of GranadaSpain
  2. 2.Department of Electrical and Computer EngineeringFAMU-FSU College of Engineering 

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