• DocumentCode
    1083206
  • Title

    Unified Pascal Matrix for First-Order s{\\hbox {\\textendash }}z Domain Transformations

  • Author

    Deng, Tian-Bo ; Chivapreecha, Sorawat ; Dejhan, Kobchai

  • Author_Institution
    Dept. of Inf. Sci., Toho Univ., Chiba
  • Volume
    57
  • Issue
    6
  • fYear
    2009
  • fDate
    6/1/2009 12:00:00 AM
  • Firstpage
    2130
  • Lastpage
    2139
  • Abstract
    The so-called generalized Pascal matrix is used for transforming a continuous-time (CT) linear system (filter) into a discrete-time (DT) one. This paper derives an explicit expression for a new generalized Pascal matrix called unified Pascal matrix from a unified first-order S-to-Z transformation model and rigorously proves the inverses for various first-order s-to-z transformations. After deriving a recurrence formula for recursively generating the inner elements of the unified Pascal matrix from its boundary elements, we also show that the recurrence formula leads to computationally unstable solutions for high-order systems due to the so-called catastrophic cancellation in numerical computation, but the unstable problem can be solved through partitioning the whole unified Pascal matrix into several small matrices (submatrices) and then using the recurrence formula to compute the submatrices individually from their boundary elements. This operation almost retains the same computational complexity while guarantees numerically stable solutions. Moreover, an interesting property of the unified Pascal matrix is proved.
  • Keywords
    boundary-elements methods; computational complexity; filtering theory; matrix algebra; catastrophic cancellation; computational complexity; continuous-time filter; continuous-time linear system; discrete-time system; first-order S-Z domain transformations; unified Pascal matrix; Continuous-time (CT) filter; discrete-time (DT) filter; one-to-one coefficient mapping; unified $s$ -to-$z$ transformation; unified Pascal matrix; unified first-order $s$-to- $z$ model;
  • fLanguage
    English
  • Journal_Title
    Signal Processing, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    1053-587X
  • Type

    jour

  • DOI
    10.1109/TSP.2009.2013895
  • Filename
    4760247