Journal of Jishou University(Natural Sciences Edition)

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Parameter Estimation Based a Conjugate Gradient Iteration Algorithm for Controlled Autoregressive Models

HU Zhizeng,LIANG Kaifu   

  1. (School of Mathematics and Computational Science,Xiangtan University,Xiangtan 411105,Hunan China)
  • Online:2016-11-25 Published:2016-12-13


The auxiliary model is derived for the single-input single-output (SISO) system to reduce computational burden and improve the convergence rate of the new iteration algorithm based on the conjugate gradient.Compared with the interactive stochastic gradient algorithm for controlled moving average models,the proposed new iteration algorithm can give parameter estimates in less steps.In addition,the new algorithm can avoid the inverse of a matrix.The new algorithm is also compared with the biconjugate gradient algorithm.The simulation example shows that the proposed algorithm works quite well.

Key words: parameter estimation, auxiliary model, conjugate gradient iterative algorithm, controlled autoregressive model

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