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A Novel Complex-Valued Fuzzy ARTMAP for Sparse Dictionary Learning

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Neural Information Processing (ICONIP 2013)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 8226))

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Abstract

This work extends the simplified fuzzy ARTMAP (SFAM) to a complex-valued (CV-SFAM) version which is able to work with spatio-temporal data produced in receptive fields of visual cortex. The CV-SFAM’s ability for incremental learning distinguishes CV-SFAM from other complex-valued neural networks, which provides the ability to preserve learned data while learning new samples. We considered different scales and orientations of Gabor wavelets to form a dictionary. This work takes advantage of a locally competitive algorithm (LCA) which calculates more regular sparse coefficients by combining the interactions of artificial neurons. Finally, we provide an experimental real application for biological implementation of sparse dictionary learning to recognize objects in both aligned and non-aligned images.

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Author information

Authors and Affiliations

  1. Faculty of Computer Science and Information Technology, University of Malaya, Kuala Lumpur, Malaysia

    Chu Kiong Loo, Ali Memariani & Wei Shiung Liew

Authors
  1. Chu Kiong Loo
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  2. Ali Memariani
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  3. Wei Shiung Liew
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Editor information

Editors and Affiliations

  1. Kyungpook National University, 1370 Sankyuk-Dong, Puk-Gu, 702-701, Taegu, Korea

    Minho Lee

  2. The University of Tokyo, 7-3-1 Hongo, 113-8656, Bunkyo-ku, Tokyo, Japan

    Akira Hirose

  3. Key Laboratory of Complex Systems and Intelligence Science, Chinese Academy of Sciences, Institute of Automation, 100190, Beijing, China

    Zeng-Guang Hou

  4. Sungkyunkwan University, 2066, Seobu-ro, Jangan-gu,, 440-746, Suwon, Korea

    Rhee Man Kil

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© 2013 Springer-Verlag Berlin Heidelberg

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Loo, C.K., Memariani, A., Liew, W.S. (2013). A Novel Complex-Valued Fuzzy ARTMAP for Sparse Dictionary Learning. In: Lee, M., Hirose, A., Hou, ZG., Kil, R.M. (eds) Neural Information Processing. ICONIP 2013. Lecture Notes in Computer Science, vol 8226. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-42054-2_45

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  • DOI: https://doi.org/10.1007/978-3-642-42054-2_45

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-42053-5

  • Online ISBN: 978-3-642-42054-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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