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Extended Kalman Filter of Training Feed Forward Artificial Neural Network

    Authors

    • Saman H. Mahmood
    • Talib S.Jalil
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Abstract

Abstract
In this paper discuss the use of artificial neural networks multilayer feed forward, which are training using and Extended Kalman Filter (EKF) algorithm one and training Back propagation algorithm standard way then compare them by using two types of data which are the original data represent time delay of the network (Aria phone) for telephone communications and simulation data. The results confirm that EKF approach is faster to the period time steps to train the neural networks compared to the second way.

Keywords

  • Dynamic Bayesian
  • Extended Kalman Filter
  • Dual Estimation
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journal of kirkuk University For Administrative and Economic Sciences
Volume 2, Issue 1
June 2012
Pages 183-201
Files
  • XML
  • PDF 967.28 K
Share
How to cite
  • RIS
  • EndNote
  • Mendeley
  • BibTeX
  • APA
  • MLA
  • HARVARD
  • VANCOUVER
Statistics
  • Article View: 289
  • PDF Download: 90

APA

H. Mahmood, S., & S.Jalil, T. (2012). Extended Kalman Filter of Training Feed Forward Artificial Neural Network. journal of kirkuk University For Administrative and Economic Sciences, 2(1), 183-201.

MLA

Saman H. Mahmood; Talib S.Jalil. "Extended Kalman Filter of Training Feed Forward Artificial Neural Network". journal of kirkuk University For Administrative and Economic Sciences, 2, 1, 2012, 183-201.

HARVARD

H. Mahmood, S., S.Jalil, T. (2012). 'Extended Kalman Filter of Training Feed Forward Artificial Neural Network', journal of kirkuk University For Administrative and Economic Sciences, 2(1), pp. 183-201.

VANCOUVER

H. Mahmood, S., S.Jalil, T. Extended Kalman Filter of Training Feed Forward Artificial Neural Network. journal of kirkuk University For Administrative and Economic Sciences, 2012; 2(1): 183-201.

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