By Xiaolin Hu, Yousheng Xia, Yunong Zhang, Dongbin Zhao
The quantity LNCS 9377 constitutes the refereed court cases of the twelfth overseas Symposium on Neural Networks, ISNN 2015, held in jeju, South Korea on October 2015. The fifty five revised complete papers provided have been rigorously reviewed and chosen from ninety seven submissions. those papers disguise many themes of neural network-related examine together with clever keep watch over, neurodynamic research, memristive neurodynamics, machine imaginative and prescient, sign processing, laptop studying, and optimization.
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Additional info for Advances in Neural Networks – ISNN 2015: 12th International Symposium on Neural Networks, ISNN 2015, Jeju, South Korea, October 15–18, 2015, Proceedings
18 C. Zheng et al. References 1. : Analysis and synthesis of Markov jump linear systems with time-varying delays and partially known transition probabilities. IEEE Trans. Auto. Con. 53, 2458–2464 (2008) 2. : Fault detection for discrete-time Markov jump linear systems with partially known transition probabilities. Int. J. Con. 83, 1564–1572 (2010) 3. : Robust stability and stabilization of discrete-time Markov jump linear systems with partly unknown transition probability matrix. In: American Control Conference (ACC), pp.
The block diagram of the proposed control system. Neural Dynamic Surface Control for PWM Rectiﬁer 33 Table 1. 1Ω DC-link capacitor 5000μF Table 2. 3 ∗ 10−7 Stability Analysis Theorem 1: Consider the closed-loop system consisting of the system (1), (2) with the virtual control law (6), the actual control laws (12), (17), the NNs (7), (13), (18), and the LTD (10). All signals in the closed-loop system are uniformly ultimately bounded, and the tracking errors of the output voltage and the q axis current can converge to a small neighborhood of the origin.
Zeng, Z. ) ISNN 2013, Part I. LNCS, vol. 7951, pp. 125–132. Springer, Heidelberg (2013) Hybrid Function Projective Synchronization of Unknown Cohen-Grossberg 27 17. : Seeking consensus in networks of linear agents: communication noises and Markovian switching topologies. IEEE Transactions on Automatic Control 60(5), 1374–1379 (2015) 18. : Consensus conditions of multi-agent systems with time-varying topologies and stochastic communication noises. IEEE Transactions on Automatic Control 55(9), 2043–2057 (2010) 19.