• DocumentCode
    1522374
  • Title

    Discretization-free design of variable fractional-delay FIR digital filters

  • Author

    Deng, Tian-Bo

  • Author_Institution
    Dept. of Inf. Sci., Toho Univ., Chiba, Japan
  • Volume
    48
  • Issue
    6
  • fYear
    2001
  • fDate
    6/1/2001 12:00:00 AM
  • Firstpage
    637
  • Lastpage
    644
  • Abstract
    This paper presents a closed-form solution for obtaining the optimal coefficients of variable finite impulse-response (FIR) filters with continuously adjustable fractional-delay (FD) response. The design is formulated as a weighted-least-squares (WLS) approximation problem without discretizing (sampling) the frequency ω and the variable FD p in the filter design process, and the objective error function of variable frequency response can be derived by numerical integration, thus the variable FD filter coefficients can be obtained in a closed-form. Compared to the existing WLS method, since the discretization-free method does not need parameter discretizations in deriving the objective error function, the closed-form solution is optimal in the sense that the filter design accuracy is not affected by the sampling grid densities, and higher design accuracy can be guaranteed. Furthermore, since the discretization-free method does not need to sum up all the squared errors at a great number of discrete points when evaluating the objective error function, the computational complexity can be reduced considerably
  • Keywords
    FIR filters; computational complexity; delays; digital filters; filtering theory; frequency response; integration; interpolation; least squares approximations; matrix algebra; FIR digital filters; WLS approximation problem; closed-form solution; computational complexity reduction; continuously adjustable fractional-delay response; discretization-free design; filter design process; finite impulse-response filters; numerical integration; objective error function; optimal coefficients; variable fractional-delay FIR digital filters; variable frequency response; weighted-least-squares approximation; Closed-form solution; Computational complexity; Digital filters; Digital signal processing; Finite impulse response filter; Frequency response; Interpolation; Lagrangian functions; Process design; Sampling methods;
  • fLanguage
    English
  • Journal_Title
    Circuits and Systems II: Analog and Digital Signal Processing, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    1057-7130
  • Type

    jour

  • DOI
    10.1109/82.943337
  • Filename
    943337