×

Delay-dependent stability criterion for bidirectional associative memory neural networks with interval time-varying delays. (English) Zbl 1214.37059

Summary: In the letter, the global asymptotic stability of bidirectional associative memory (BAM) neural networks with delays is investigated. The delay is assumed to be time-varying and belongs to a given interval. A novel stability criterion for the stability is presented based on the Lyapunov method. The criterion is represented in terms of linear matrix inequality (LMI), which can be solved easily by various optimization algorithms. Two numerical examples are illustrated to show the effectiveness of our new result.

MSC:

37N35 Dynamical systems in control
93D20 Asymptotic stability in control theory
93D15 Stabilization of systems by feedback
92B10 Taxonomy, cladistics, statistics in mathematical biology
93D05 Lyapunov and other classical stabilities (Lagrange, Poisson, \(L^p, l^p\), etc.) in control theory

Software:

LMI toolbox
PDFBibTeX XMLCite
Full Text: DOI

References:

[1] DOI: 10.1016/S0375-9601(03)00569-3 · Zbl 1098.92501
[2] Zhang Y., Neurocomputing
[3] DOI: 10.1016/j.chaos.2005.11.040 · Zbl 1127.93352
[4] DOI: 10.1016/j.physleta.2005.12.031 · Zbl 1187.34103
[5] DOI: 10.1016/j.physleta.2005.05.016 · Zbl 1222.93178
[6] DOI: 10.1364/AO.26.004947
[7] DOI: 10.1109/21.87054
[8] DOI: 10.1073/pnas.81.10.3088 · Zbl 1371.92015
[9] DOI: 10.1109/72.329700
[10] DOI: 10.1103/PhysRevE.61.1825
[11] DOI: 10.1016/j.physleta.2003.08.019 · Zbl 1046.68090
[12] DOI: 10.1016/S0016-0032(98)00040-4 · Zbl 0969.34066
[13] DOI: 10.1023/A:1021781602182 · Zbl 0947.65088
[14] DOI: 10.1080/002077200412113 · Zbl 1080.93598
[15] DOI: 10.1023/A:1026470106976 · Zbl 0981.93069
[16] DOI: 10.1016/S0096-3003(03)00224-8 · Zbl 1036.93054
[17] DOI: 10.1023/B:JOTA.0000026135.99294.32 · Zbl 1061.93079
[18] DOI: 10.1007/s10957-005-5501-9 · Zbl 1159.34344
[19] DOI: 10.1002/(SICI)1097-007X(199805/06)26:3<219::AID-CTA991>3.0.CO;2-I · Zbl 0915.94012
[20] DOI: 10.1016/S0375-9601(02)00434-6 · Zbl 0995.92002
[21] DOI: 10.1016/S0960-0779(04)00561-2
[22] DOI: 10.1016/j.physleta.2005.10.059 · Zbl 1234.34048
[23] DOI: 10.1016/S0096-3003(02)00308-9 · Zbl 1031.34074
[24] DOI: 10.1016/S0096-3003(02)00095-4 · Zbl 1034.34087
[25] DOI: 10.1016/j.chaos.2005.08.018 · Zbl 1121.92006
[26] DOI: 10.1016/j.neucom.2004.12.002 · Zbl 05011764
[27] DOI: 10.1016/j.chaos.2004.03.004 · Zbl 1062.68102
[28] DOI: 10.1016/j.chaos.2004.09.037 · Zbl 1071.82538
[29] DOI: 10.1016/j.neucom.2006.02.020 · Zbl 05184828
[30] DOI: 10.1016/j.physleta.2005.09.067
[31] DOI: 10.1016/j.chaos.2007.01.002 · Zbl 1146.93366
[32] Qiu J., Chaos, Solitons & Fractals
[33] DOI: 10.1016/j.cam.2007.03.009 · Zbl 1136.93437
[34] DOI: 10.1049/ip-cta:20050294
[35] DOI: 10.1137/1.9781611970777 · Zbl 0816.93004
[36] Gahinet P., LMI Control Toolbox User’s Guide (1995)
This reference list is based on information provided by the publisher or from digital mathematics libraries. Its items are heuristically matched to zbMATH identifiers and may contain data conversion errors. In some cases that data have been complemented/enhanced by data from zbMATH Open. This attempts to reflect the references listed in the original paper as accurately as possible without claiming completeness or a perfect matching.