期刊
NEURAL NETWORKS
卷 69, 期 -, 页码 44-50出版社
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.neunet.2015.05.003
关键词
Complex-valued neural networks; Augmented algorithm; Unified mean value theorem; Wirtinger calculus; Convergence
资金
- National Natural Science Foundation of China [61301202, 61101228]
- Doctoral Program of Higher Education of China [20122304120028]
This paper presents an augmented algorithm for fully complex-valued neural network based on Wirtinger calculus, which simplifies the derivation of the algorithm and eliminates the Schwarz symmetry restriction on the activation functions. A unified mean value theorem is first established for general functions of complex variables, covering the analytic functions, non-analytic functions and real-valued functions. Based on so introduced theorem, convergence results of the augmented algorithm are obtained under mild conditions. Simulations are provided to support the analysis. (C) 2015 Elsevier Ltd. All rights reserved.
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