• DocumentCode
    1812774
  • Title

    Stochastic approximation for function minimization under quantization error

  • Author

    Gerencsér, László ; Vágó, Zsuzsanna

  • Author_Institution
    Comput. & Autom. Inst., Hungarian Acad. of Sci., Budapest, Hungary
  • Volume
    3
  • fYear
    1999
  • fDate
    1999
  • Firstpage
    2373
  • Abstract
    The simultaneous perturbation stochastic approximation (SPSA) method developed by Spall (1992) is applied and analyzed for function minimization under quantization error. It is proved that under certain conditions the estimator sequence converges with rate O(n-β/2 ) for some β>0, where the rate is measured by the Lq -norm of the estimation error for any 1⩽q<∞. The viability of SPSA for the present problem is also demonstrated by simulation results
  • Keywords
    approximation theory; convergence of numerical methods; minimisation; noise; quantisation (signal); stochastic processes; Kiefer Wolfovitz method; SPSA method; convergence; minimization; noise distribution; optimisation; perturbation; quantization; stochastic approximation; Additive noise; Automation; Estimation error; Linear regression; Minimization methods; Noise measurement; Quantization; Stochastic processes; Vibration measurement; Working environment noise;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Decision and Control, 1999. Proceedings of the 38th IEEE Conference on
  • Conference_Location
    Phoenix, AZ
  • ISSN
    0191-2216
  • Print_ISBN
    0-7803-5250-5
  • Type

    conf

  • DOI
    10.1109/CDC.1999.831279
  • Filename
    831279
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=1812774