What is it about?
The research is on the stochastic stability problem for neutral-type markovian jump neural networks with additive time-varying delasy
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Why is it important?
To obtain less conservative delay-dependent stability condition, this paper introduce an important and novel inequality about reciprocally convex combination to deal with the delayed dynamic systems with two and more delays.
Perspectives
Writing this article was a great pleasure as it have co-authors with whom I have had long standing collaborations. This article also lead to markovian jump systems with additive time-varying delays groups contacting me and ultimately to a greater involvement in markovian jump systems with additive time-varying delays research.
Lianglin Xiong
Yunnan Minzu University
Read the Original
This page is a summary of: Stochastic stability analysis for neutral-type Markov jump neural networks with additive time-varying delays via a new reciprocally convex combination inequality, International Journal of Systems Science, March 2019, Taylor & Francis,
DOI: 10.1080/00207721.2019.1586005.
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