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Structure Determination of a Generalized ADALINE Neural Network for Application in System Identification of Linear Systems

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Advances in Swarm and Computational Intelligence (ICSI 2015)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 9142))

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Abstract

This paper presents a structure determination method of a GADALINE based neural network used for linear system identification and parameter estimation. In GADALINE linear system identification, the past input data are used as its input and the past output data are also used as its input in the form of feedback because in such a linear system, the current system output is dependent on past outputs and on both the current and past inputs. The structure determination is then to determine how many past inputs should be included as its input and how many past output should be fed-back as its input also. The measured data set can then be used to train the GADALINE and during training, the performance error can be used to determine the network structure in our method just as the Final Prediction Error used in Akaike’s criterion. One advantage of the method is its simplicity. Simulation results show that the proposed method provides satisfactory performance.

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Author information

Authors and Affiliations

  1. Department of Engineering Technology, University of Arkansas at Little Rock, Little Rock, AR, 72204, USA

    Wenle Zhang

Authors
  1. Wenle Zhang
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Corresponding author

Correspondence to Wenle Zhang .

Editor information

Editors and Affiliations

  1. Peking University, Beijing, China

    Ying Tan

  2. Xi'an Jiaotong-Liverpool University, Suzhou, China

    Yuhui Shi

  3. Universidade de Pernambuco, Recife, Brazil

    Fernando Buarque

  4. Instituto Politécnico Nacional, Mexico, Mexico

    Alexander Gelbukh

  5. Indian Statistical Institute, Kolkata, India

    Swagatam Das

  6. University of Pretoria, Pretoria, South Africa

    Andries Engelbrecht

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Zhang, W. (2015). Structure Determination of a Generalized ADALINE Neural Network for Application in System Identification of Linear Systems. In: Tan, Y., Shi, Y., Buarque, F., Gelbukh, A., Das, S., Engelbrecht, A. (eds) Advances in Swarm and Computational Intelligence. ICSI 2015. Lecture Notes in Computer Science(), vol 9142. Springer, Cham. https://doi.org/10.1007/978-3-319-20469-7_3

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  • DOI: https://doi.org/10.1007/978-3-319-20469-7_3

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-20468-0

  • Online ISBN: 978-3-319-20469-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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