本文關(guān)鍵詞：幾類反應(yīng)擴散神經(jīng)網(wǎng)絡(luò)的控制與同步　出處：《新疆大學(xué)》2017年碩士論文　論文類型：學(xué)位論文

  更多相關(guān)文章： 反應(yīng)擴散神經(jīng)網(wǎng)絡(luò) 牽制脈沖控制 間歇采樣控制 自適應(yīng)間歇控制 同步

【摘要】：反應(yīng)擴散神經(jīng)網(wǎng)絡(luò)的控制與同步是當今神經(jīng)網(wǎng)絡(luò)動力學(xué)研究的熱點問題之一,越來越受到國內(nèi)外學(xué)者的廣泛關(guān)注.本文通過設(shè)計不同的離散型控制器,分別研究了具有混合時滯的BAM反應(yīng)擴散神經(jīng)網(wǎng)絡(luò)的牽制脈沖控制、具有時滯的混合耦合反應(yīng)擴散神經(jīng)網(wǎng)絡(luò)的間歇采樣同步以及具有切換拓撲的耦合反應(yīng)擴散神經(jīng)網(wǎng)絡(luò)的自適應(yīng)間歇同步.本文的主要工作概括如下:在第1節(jié)引言中,論述了反應(yīng)擴散神經(jīng)網(wǎng)絡(luò)動力學(xué)的研究背景和研究現(xiàn)狀,介紹了控制與同步反應(yīng)擴散神經(jīng)網(wǎng)絡(luò)的常用方法,并提出了本文的研究內(nèi)容.在第2節(jié)中,利用牽制脈沖控制,對具有混合時滯的BAM反應(yīng)擴散神經(jīng)網(wǎng)絡(luò)進行了指數(shù)穩(wěn)定化.在設(shè)計的控制器中,脈沖控制函數(shù)可以是非線性的,并且我們是依據(jù)系統(tǒng)狀態(tài)誤差在每一個脈沖點的重新排序來選取有哪些神經(jīng)元將受到牽制.此外,基于所設(shè)計的控制器和Lyapunov函數(shù),我們得到了一系列依賴于擴散系數(shù)和控制參數(shù)的網(wǎng)絡(luò)全局指數(shù)穩(wěn)定判別準則.最后,通過兩個例子驗證了理論結(jié)果的正確性.在第3節(jié)中,通過具有空間采樣的間歇控制,研究了具有時滯的混合耦合反應(yīng)擴散神經(jīng)網(wǎng)絡(luò)的指數(shù)同步問題,得到了一系列使得網(wǎng)絡(luò)指數(shù)同步的充分條件,這些條件不但依賴于時滯和擴散系數(shù),還依賴于網(wǎng)絡(luò)的耦合強度.此外,本節(jié)中所運用的控制方法,不僅包含了周期和非周期兩種間歇控制,而且,在沿時間方向進行間歇控制的同時,還沿空間方向進行了采樣控制.在本節(jié)的最后,我們通過數(shù)值仿真實驗驗證了間歇采樣控制的可行性和有效性.在第4節(jié)中,通過常增益間歇控制和自適應(yīng)間歇控制,討論了具有切換拓撲的耦合反應(yīng)擴散神經(jīng)網(wǎng)絡(luò)的同步問題,得到了一系列依賴于擴散系數(shù)和網(wǎng)絡(luò)耦合強度的網(wǎng)絡(luò)同步判別準則.而在自適應(yīng)間歇控制中,自適應(yīng)控制增益不僅與時間有關(guān),還與空間變量有關(guān).最后,我們對本節(jié)的主要結(jié)果進行了數(shù)據(jù)模擬.
[Abstract]:The control and synchronization of reaction-diffusion neural networks (RNN) is one of the hot issues in the research of neural network dynamics, and has attracted more and more attention from scholars at home and abroad. In this paper, different discrete controllers are designed. In this paper, the control of BAM reaction-diffusion neural networks with mixed delay is studied. The intermittent sampling synchronization of a hybrid coupled reaction diffusion neural network with time delay and the adaptive intermittent synchronization of a coupled reaction-diffusion neural network with switching topology are presented. The main work of this paper is summarized as follows:. In the introduction to section 1. This paper discusses the research background and present situation of the dynamics of reactive diffusion neural networks, introduces the common methods of controlling and synchronizing the reaction diffusion neural networks, and puts forward the research contents of this paper. The BAM reaction-diffusion neural network with mixed time delay is exponentially stabilized by the choke pulse control. In the designed controller, the pulse control function can be nonlinear. And we select which neurons will be restrained according to the reordering of system state error at each pulse point. In addition, based on the designed controller and Lyapunov function. We obtain a series of global exponential stability criteria which depend on the diffusion coefficient and control parameters. Finally, two examples are given to verify the correctness of the theoretical results. By means of intermittent control with spatial sampling, the exponential synchronization problem of hybrid coupled reaction diffusion neural networks with time delay is studied, and a series of sufficient conditions for exponential synchronization of the networks are obtained. These conditions depend not only on the delay and diffusion coefficient, but also on the coupling strength of the network. In addition, the control methods used in this section include not only periodic and aperiodic intermittent control, but also. At the same time of intermittent control along the direction of time, sampling control is also carried out along the direction of space. At the end of this section. The feasibility and effectiveness of intermittent sampling control are verified by numerical simulation. In section 4, we use constant gain intermittent control and adaptive intermittent control. In this paper, the synchronization problem of coupled reactive diffusion neural networks with switching topology is discussed. A series of network synchronization criteria dependent on diffusion coefficient and network coupling strength are obtained, but in adaptive intermittent control. The adaptive control gain is not only related to time, but also to spatial variables. Finally, we simulate the main results of this section.
【學(xué)位授予單位】：新疆大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2017
【分類號】：O175;O231

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相關(guān)博士學(xué)位論文 前1條

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本文編號：1396528