LMI conditions for global robust stability of delayed neural networks with discontinuous neuron activations. Guo, Z. & Huang, L. Applied Mathematics and Computation, 215(3):889–900, October, 2009.
Paper doi abstract bibtex Without assuming that the neuron activations are bounded, some delay-independent criteria for interval delayed neural networks with discontinuous neuron activations are derived to guarantee global robust stability by using the generalized Lyapunov method and linear matrix inequality (LMI) technique. The obtained results improve and extend those given in earlier literature, and two numerical examples are also given to show the effectiveness of our results.
@article{guo_lmi_2009,
title = {{LMI} conditions for global robust stability of delayed neural networks with discontinuous neuron activations},
volume = {215},
issn = {00963003},
url = {https://linkinghub.elsevier.com/retrieve/pii/S009630030900575X},
doi = {10.1016/j.amc.2009.06.013},
abstract = {Without assuming that the neuron activations are bounded, some delay-independent criteria for interval delayed neural networks with discontinuous neuron activations are derived to guarantee global robust stability by using the generalized Lyapunov method and linear matrix inequality (LMI) technique. The obtained results improve and extend those given in earlier literature, and two numerical examples are also given to show the effectiveness of our results.},
language = {en},
number = {3},
urldate = {2022-01-19},
journal = {Applied Mathematics and Computation},
author = {Guo, Zhenyuan and Huang, Lihong},
month = oct,
year = {2009},
keywords = {/unread},
pages = {889--900},
}
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