Introduction

  • Ba-Ngu Vo
  • Antonio Cantoni
  • Kok Lay Teo
Part of the Applied Optimization book series (APOP, volume 56)

Abstract

In signal processing, the design of many filters can often be cast as a constrained optimization problem where the constraints are defined by the specifications of the filter. These specifications can arise either from practical considerations or from the standards set by certain regulatory bodies. Traditional filter design techniques are developed in the frequency domain where the response of a filter at a particular frequency is dependent solely on the excitation of that frequency. This is not true with time domain problems. Clearly, an excitation applied at any time will have effects on the response at all times after the application of the excitation. Conversely, the response at any particular instant depends on all the excitations that have been applied to the filter prior to that instant. This difference manifests mathematically in the form of multiplication and convolution.

Keywords

Impulse Response Pulse Shape Finite Impulse Response Matched Filter Pulse Compression 
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 Science+Business Media Dordrecht 2001

Authors and Affiliations

  • Ba-Ngu Vo
    • 1
  • Antonio Cantoni
    • 2
  • Kok Lay Teo
    • 3
  1. 1.The University of MelbourneAustralia
  2. 2.The University of Western AustraliaAustralia
  3. 3.The Hong Kong Polytechnic UniversityHong Kong

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