Advances in Neural Networks – ISNN 2009: 6th International by Mingchang Li, Guangyu Zhang, Bin Zhou, Shuxiu Liang,
By Mingchang Li, Guangyu Zhang, Bin Zhou, Shuxiu Liang, Zhaochen Sun (auth.), Wen Yu, Haibo He, Nian Zhang (eds.)
The 3 quantity set LNCS 5551/5552/5553 constitutes the refereed court cases of the sixth overseas Symposium on Neural Networks, ISNN 2009, held in Wuhan, China in may perhaps 2009.
The 409 revised papers awarded have been conscientiously reviewed and chosen from a complete of 1.235 submissions. The papers are equipped in 20 topical sections on theoretical research, balance, time-delay neural networks, laptop studying, neural modeling, selection making structures, fuzzy structures and fuzzy neural networks, help vector machines and kernel equipment, genetic algorithms, clustering and category, trend reputation, clever keep an eye on, optimization, robotics, picture processing, sign processing, biomedical functions, fault analysis, telecommunication, sensor community and transportation structures, in addition to applications.
Read or Download Advances in Neural Networks – ISNN 2009: 6th International Symposium on Neural Networks, ISNN 2009 Wuhan, China, May 26-29, 2009 Proceedings, Part I PDF
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Additional info for Advances in Neural Networks – ISNN 2009: 6th International Symposium on Neural Networks, ISNN 2009 Wuhan, China, May 26-29, 2009 Proceedings, Part I
1 Introduction To our knowledge, the conventional gradient or gradient-based neural networks (GNN) could be viewed as a useful and important method for time-invariant problems solving [1,2]. However, many time-varying problems intrinsically exist in mathematics, science and engineering areas [2,3,4,5,6], such as the timevarying matrix square roots (TVMSR) problem depicted as below: X 2 (t) − A(t) = 0, t ∈ [0, +∞), (1) where, being a smoothly time-varying positive-deﬁnite matrix, A(t) ∈ Rn×n and ˙ its time derivative A(t) are both assumed known numerically (or at least measurable accurately).
Overall GNN Simulink model applied to time-varying square roots solving 5) The MATLAB Fcn block can be used to generate matrix A(t) with the Clock block’s output as its input or can be used to compute the matrix norm. 6) The Math Function block can perform various common mathematical operations, and, in our context, generates the transpose of a matrix and so on. 7) The To Workspace block, with its option “Save format” set to be “Array”, is used to save the modeling results and data to the workspace.
6 0 20 40 60 80 100 120 140 Time (Hours) Fig. 4. Comparison of tidal current for 69# Table 1. 4 Table 2. Values for phase (º)of control nodes along open boundary Tidal constituents M2 K1 Qinghuang dao -140 -155 -170 120 135 150 Changxing dao 50 65 80 30 45 60 Tidal constituents S2 O1 Qinghuang dao -60 -75 -89 10 25 40 Changxing dao 100 115 130 55 70 85 An interesting phenomenon is founded by analyzing the result of designed cases, that is the tidal amplitude is not affected by the change of tidal phase in its assumed range.