• DocumentCode
    1915620
  • Title

    A two-processing element adaptable linear oscillating recurrent system with single-weight plasticity

  • Author

    Johnson, Michael R. ; Principe, Jose C.

  • Author_Institution
    Florida Univ., Gainesville, FL, USA
  • Volume
    1
  • fYear
    2003
  • fDate
    20-24 July 2003
  • Firstpage
    51
  • Abstract
    A simple recursive linear two-processing element adaptable oscillator is developed and demonstrated. Simple harmonic motion and its mathematical description is the foundation of this study. State equations for an undamped spring-mass system are converted to a discrete time system, followed by eigenvalue analysis to convert the four-degree-of-freedom system to a recursive network with plasticity in one variable. The oscillator is initialized to a frequency in the neighborhood of the desired frequency, and tuned by using resilient backpropagation modified for backpropagation through time. It is shown that the network can track frequencies in a spectrum of operation as defined by the sampling frequency, given the network is initialized to frequencies in the neighborhood of those of interest.
  • Keywords
    adaptive systems; backpropagation; discrete time systems; eigenvalues and eigenfunctions; linear systems; oscillators; recurrent neural nets; adaptable linear system; discrete time system; eigenvalue analysis; oscillation; recurrent system; recursive oscillator; resilient backpropagation; single-weight plasticity; two-processing element system; Backpropagation; Circuits; Difference equations; Differential equations; Discrete time systems; Eigenvalues and eigenfunctions; Frequency; Inhibitors; Oscillators; Sampling methods;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Neural Networks, 2003. Proceedings of the International Joint Conference on
  • ISSN
    1098-7576
  • Print_ISBN
    0-7803-7898-9
  • Type

    conf

  • DOI
    10.1109/IJCNN.2003.1223286
  • Filename
    1223286