Literature DB >> 25314711

Fractional extreme value adaptive training method: fractional steepest descent approach.

Yi-Fei Pu, Ji-Liu Zhou, Yi Zhang, Ni Zhang, Guo Huang, Patrick Siarry.   

Abstract

The application of fractional calculus to signal processing and adaptive learning is an emerging area of research. A novel fractional adaptive learning approach that utilizes fractional calculus is presented in this paper. In particular, a fractional steepest descent approach is proposed. A fractional quadratic energy norm is studied, and the stability and convergence of our proposed method are analyzed in detail. The fractional steepest descent approach is implemented numerically and its stability is analyzed experimentally.

Year:  2013        PMID: 25314711     DOI: 10.1109/TNNLS.2013.2286175

Source DB:  PubMed          Journal:  IEEE Trans Neural Netw Learn Syst        ISSN: 2162-237X            Impact factor:   10.451


  1 in total

1.  Fractional-Order Deep Backpropagation Neural Network.

Authors:  Chunhui Bao; Yifei Pu; Yi Zhang
Journal:  Comput Intell Neurosci       Date:  2018-07-03
  1 in total

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