✦ LIBER ✦

Mean-square exponential input-to-state stability of stochastic delayed neural networks

✍ Scribed by Zhu, Quanxin; Cao, Jinde

Book ID: 121843349
Publisher: Elsevier Science
Year: 2014
Tongue: English
Weight: 503 KB
Volume: 131
Category: Article
ISSN: 0925-2312
DOI: 10.1016/j.neucom.2013.10.029

No coin nor oath required. For personal study only.

📜 SIMILAR VOLUMES

Mean square exponential stability of unc

Mean square exponential stability of uncertain stochastic delayed neural networks

✍ Wu-Hua Chen; Xiaomei Lu 📂 Article 📅 2008 🏛 Elsevier Science 🌐 English ⚖ 173 KB

Further results on mean square exponenti

Further results on mean square exponential stability of uncertain stochastic delayed neural networks

✍ Jianjiang Yu; Kanjian Zhang; Shumin Fei 📂 Article 📅 2009 🏛 Elsevier Science 🌐 English ⚖ 215 KB

Mean Square Exponential Stability for Un

Mean Square Exponential Stability for Uncertain Delayed Stochastic Neural Networks with Markovian Jump Parameters

✍ Qi Zhou; Bing Chen; Chong Lin; Hongyi Li 📂 Article 📅 2010 🏛 Springer 🌐 English ⚖ 359 KB

Mean square exponential stability of gen

Mean square exponential stability of generalized stochastic neural networks with time-varying delays

✍ Jianjiang Yu; Kanjian Zhang; Shumin Fei 📂 Article 📅 2009 🏛 John Wiley and Sons 🌐 English ⚖ 204 KB

Mean square exponential stability of unc

Mean square exponential stability of uncertain stochastic neural networks with time-varying delay

✍ Yuanyuan Wu; Yuqiang Wu; Yonggang Chen 📂 Article 📅 2009 🏛 Elsevier Science 🌐 English ⚖ 195 KB

Mean square exponential stability of sto

Mean square exponential stability of stochastic recurrent neural networks with time-varying delays

✍ Chuangxia Huang; Yigang He; Hainu Wang 📂 Article 📅 2008 🏛 Elsevier Science 🌐 English ⚖ 288 KB

The stability of a class of stochastic Recurrent Neural Networks with time-varying delays is investigated in this paper. With the help of the Lyapunov function and the Dini derivative of the expectation of V (t, X (t)) ''along'' the solution X (t) of the model, a set of novel sufficient conditions o