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A Novel CFNN Model for Designing Complex FIR Digital Filters

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Advances in Natural Computation (ICNC 2006)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 4221))

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Abstract

A complex feedforward neural network (CFNN) model is proposed via energy function optimum theory and the complex frequency response of complex finite impulse response (FIR) digital filter. Then the convergence of the model is proved, and the universality of the model is studied. Simulation results show that the proposed CFNN model can achieve a good approach to an arbitrary digital filter and has universal performance.

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References

  1. Yumei, D., Xiquan, G.: Digital Signal Processing, pp. 195–197. Xidian University Press, Xi’an (2001)

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Author information

Authors and Affiliations

  1. Air Force Radar Academy, Wuhan, 430019, China

    Ma Xiaoyan, Yang Jun, He Zhaohui & Qin Jiangmin

Authors
  1. Ma Xiaoyan
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  2. Yang Jun
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  3. He Zhaohui
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  4. Qin Jiangmin
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Editor information

Editors and Affiliations

  1. Life Science Research Center, School of Electronic Engineering, Xidian University, 710071, Xi’an, Shaanxi, China

    Licheng Jiao

  2. School of Electrical and Electronic Engineering, Nanyang Technological University, Block S1, Nanyang Avenue, 639798, Singapore

    Lipo Wang

  3. School of Electronic Engineering, Xidian Univ., 710071, Xi’an, P.R. China

    Xin-bo Gao

  4. College of Mathematics and Information Science, Hebei Normal University, 050016, Shijiazhuang, Hebei, P.R. China

    Jing Liu

  5. Multi-Agent Systems Lab,Department of Computer Science, University of Science and Technology of China, 230026, Hefei, China

    Feng Wu

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© 2006 Springer-Verlag Berlin Heidelberg

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Xiaoyan, M., Jun, Y., Zhaohui, H., Jiangmin, Q. (2006). A Novel CFNN Model for Designing Complex FIR Digital Filters. In: Jiao, L., Wang, L., Gao, Xb., Liu, J., Wu, F. (eds) Advances in Natural Computation. ICNC 2006. Lecture Notes in Computer Science, vol 4221. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11881070_12

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  • DOI: https://doi.org/10.1007/11881070_12

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-45901-9

  • Online ISBN: 978-3-540-45902-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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