發(fā)布時(shí)間：2018-04-04 11:37

  本文選題：復(fù)值神經(jīng)網(wǎng)絡(luò)　切入點(diǎn)：時(shí)滯　出處：《集美大學(xué)》2017年碩士論文

【摘要】：眾所周知,時(shí)滯的存在可能導(dǎo)致神經(jīng)網(wǎng)絡(luò)系統(tǒng)不穩(wěn)定,因而研究基于時(shí)滯的穩(wěn)定性不僅具有理論價(jià)值也具有實(shí)際應(yīng)用價(jià)值.同時(shí)由于復(fù)值神經(jīng)網(wǎng)絡(luò)比實(shí)值神經(jīng)網(wǎng)絡(luò)更具有一般性,能解決實(shí)值神經(jīng)網(wǎng)絡(luò)不能解決的問題.因此,具有時(shí)滯的復(fù)值神經(jīng)網(wǎng)絡(luò)穩(wěn)定性成為了學(xué)者們研究的熱點(diǎn).基于前人的基礎(chǔ),我們將研究具有時(shí)滯的復(fù)值神經(jīng)網(wǎng)絡(luò)的穩(wěn)定性并給出相關(guān)的穩(wěn)定性判據(jù).本文研究了具有時(shí)滯的復(fù)值神經(jīng)網(wǎng)絡(luò)的穩(wěn)定性問題,主要內(nèi)容包含三個(gè)方面:(1)研究了時(shí)標(biāo)上具有時(shí)滯的復(fù)值遞歸神經(jīng)網(wǎng)絡(luò)全局指數(shù)穩(wěn)定性.基于時(shí)標(biāo)理論和壓縮映射,不僅給出了解的存在唯一性條件且討論了其指數(shù)穩(wěn)定性.(2)研究了具有時(shí)滯的不連續(xù)復(fù)值神經(jīng)網(wǎng)絡(luò)的周期解的全局指數(shù)穩(wěn)定性.運(yùn)用Lyapunov穩(wěn)定性方法,獲得了周期解的一些準(zhǔn)則并證明周期解的全局指數(shù)穩(wěn)定性.(3)研究了具有比例時(shí)滯的復(fù)值神經(jīng)網(wǎng)絡(luò)的全局指數(shù)穩(wěn)定性和周期性.利用Lyapunov穩(wěn)定性方法,獲得了該系統(tǒng)具有指數(shù)穩(wěn)定性和周期性的新標(biāo)準(zhǔn).
[Abstract]:It is well known that the existence of time delay may lead to the instability of neural network systems, so the study of the stability based on time delay has not only theoretical value but also practical application value.Because the complex neural network is more general than the real value neural network, it can solve the problems that can not be solved by the real value neural network.Therefore, the stability of complex valued neural networks with time delay has become a hot topic.Based on the previous results, we will study the stability of complex valued neural networks with time delay and give the relevant stability criteria.In this paper, the stability of complex valued neural networks with time delay is studied. The main contents include three aspects: 1) the global exponential stability of complex recurrent neural networks with time delays on time scales is studied.Based on time scale theory and contraction mapping, not only the existence and uniqueness conditions of solution are given, but also its exponential stability is discussed. (2) the global exponential stability of periodic solutions of discontinuous complex neural networks with time delay is studied.By using the Lyapunov stability method, some criteria of periodic solutions are obtained and the global exponential stability of periodic solutions is proved. 3) the global exponential stability and periodicity of complex neural networks with proportional delays are studied.A new criterion for exponential stability and periodicity of the system is obtained by using the Lyapunov stability method.
【學(xué)位授予單位】：集美大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2017
【分類號(hào)】：O175

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本文編號(hào)：1709795