NDLI: Proposal, verification and comparison on infinitely many ZTFs leading to various nets for Zhang matrix inverse solving

Content Provider	IEEE Xplore Digital Library
Author	Binbin Qiu Yunong Zhang Zhi Yang
Copyright Year	2015
Description	Author affiliation: Sch. of Inf. Sci. & Technol., Sun Yat-sen Univ., Guangzhou, China (Binbin Qiu; Yunong Zhang; Zhi Yang)
Abstract	Lately, Zhang et al have proposed the notion of infinitely many Z-type functions (ZTFs) leading to various Z-type neural nets (ZTNNs), and established a systematic approach (i.e., the general-form ZTNN, GFZTNN) for the real-time solution of a time-varying matrix inverse (also termed, Zhang matrix inverse, ZMI). Being a supplementary and in-depth research, this paper provides the theoretical result on the convergence performance of the GFZTNN model. Besides, such a GFZTNN model is generalized and exploited for computing the time-varying Drazin inverse (TVDI) instead of the usual constant one. Finally, computer simulations with two illustrative examples are performed to show the efficacy and advantage of two specific ZTNN models originating from the GFZTNN model for the realtime solution of ZMI and/or TVDI.
Starting Page	354
Ending Page	361
File Size	286362
Page Count	8
File Format	PDF
ISBN	9781479917150
e-ISBN	9781479917174
DOI	10.1109/ICICIP.2015.7388196
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2015-11-26
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Z-type neural nets (ZTNNs) Time-varying Drazin inverse (TVDI) Analytical models Computational modeling Neural networks Z-type functions (ZTFs) Real-time systems Eigenvalues and eigenfunctions Verification and comparison Numerical models Zhang matrix inverse (ZMI) Convergence
Content Type	Text
Resource Type	Article

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