Journal
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS
Volume 25, Issue 10, Pages 1936-1941Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TNNLS.2013.2296514
Keywords
Dissipativity; neural networks; passivity; stability
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Funding
- Basic Science Research Program through the National Research Foundation of Korea - Ministry of Education [2013R1A1A2A10005201]
- National Research Foundation of Korea [2013R1A1A2A10005201, 22A20130000136] Funding Source: Korea Institute of Science & Technology Information (KISTI), National Science & Technology Information Service (NTIS)
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In this brief, an extended dissipativity analysis was conducted for a neural network with time-varying delays. The concept of the extended dissipativity can be used to solve for the H infinity, L-2-L-infinity, passive, and dissipative performance by adjusting the weighting matrices in a new performance index. In addition, the activation function dividing method is modified by introducing a tuning parameter. Examples are provided to show the effectiveness and less conservatism of the proposed method.
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