王繼禹,賈秀玲,佘連兵
(1.河南理工大學(xué)萬方科技學(xué)院,公共基礎(chǔ)部,河南鄭州 451400;2.六盤水師范學(xué)院數(shù)學(xué)系,貴州六盤水 553004)
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含有變時(shí)滯的非自治BAM神經(jīng)網(wǎng)絡(luò)周期解的全局指數(shù)穩(wěn)定性
王繼禹1,賈秀玲1,佘連兵2
(1.河南理工大學(xué)萬方科技學(xué)院,公共基礎(chǔ)部,河南鄭州451400;2.六盤水師范學(xué)院數(shù)學(xué)系,貴州六盤水553004)
利用M矩陣?yán)碚撘约癏alanay不等式技巧,給出了一類含有變時(shí)滯的非自治BAM神經(jīng)網(wǎng)絡(luò)周期解的全局指數(shù)穩(wěn)定的充分條件,這些條件去掉了對(duì)激活函數(shù)的有界性、單調(diào)性和可微性的要求.
BAM神經(jīng)網(wǎng)絡(luò);周期解;M矩陣;全局指數(shù)穩(wěn)定性
雙向聯(lián)想記憶神經(jīng)網(wǎng)絡(luò)(BAM)模型自從1988年被Kosko[1]提出以來,已在模式識(shí)別、智能處理、優(yōu)化計(jì)算以及復(fù)雜控制等領(lǐng)域得到廣泛應(yīng)用.雙向聯(lián)想記憶神經(jīng)網(wǎng)絡(luò)已經(jīng)引起了眾多研究者的關(guān)注[2-7],但在現(xiàn)實(shí)應(yīng)用中,人們發(fā)現(xiàn)時(shí)滯往往不可避免地出現(xiàn)在神經(jīng)網(wǎng)絡(luò)中,從而引起許多振蕩和不穩(wěn)定現(xiàn)象.文獻(xiàn)[7]對(duì)時(shí)滯的雜交雙向聯(lián)想記憶神經(jīng)網(wǎng)絡(luò)(BAM)周期解的穩(wěn)定性進(jìn)行了研究,給出了一些新的結(jié)果.受文獻(xiàn)[2-7]的啟發(fā),本文研究如下神經(jīng)網(wǎng)絡(luò)模型:
(1)
其中i=1,2,…,n;j=1,2,…,m.這里xi(t),yj(t)分別表示第i和第j個(gè)神經(jīng)元在t時(shí)刻神經(jīng)細(xì)胞的狀態(tài);ai(t)>0,bj(t)>0,cij(t),dji(t),pij(t),qji(t)表示t時(shí)刻的聯(lián)接權(quán)值;fj,gi為激活函數(shù);τij(t),σji(t)是以ω為周期的信號(hào)傳輸時(shí)滯;Ii(t),Jj(t)分別是t時(shí)刻的外部輸入.
系統(tǒng)(1)的初始條件為
這里φi(t),ψj(t)是定義在[-σ,0]和[-τ,0]上的實(shí)值連續(xù)函數(shù).
本文假設(shè)激活函數(shù)、信號(hào)傳輸時(shí)滯函數(shù)和聯(lián)接權(quán)值函數(shù)滿足如下條件:
(H1)存在正常數(shù)Li,Mj,使對(duì)任意的x,y∈R.
(H2)0≤τij(t)≤τ,0≤σji(t)≤σ.
為方便起見,記
定義1若存在常數(shù)κ≥1和ε>0滿足
則稱系統(tǒng)(1)是指數(shù)穩(wěn)定的,其中
這里r>1,r∈R.記
則(x*(t),y*(t))T是系統(tǒng)(1)的一個(gè)ω周期解.
定義2設(shè)實(shí)矩陣S=(sij)n×n的非主對(duì)角線元非正,且逆矩陣為非負(fù)矩陣,即當(dāng)i≠j時(shí),sij≤0且S-1≥0,則稱S為M矩陣.
引理1[7]若a>0,b>0,p>0,q>0,p+q=1,則apbq≤pa+qb.
引理2[7]設(shè)Z(t)滿足不等式:
定理1若(H1)~(H3)成立,且存在實(shí)數(shù)αij,α*ij,βij,β*ij,ηji,η*ji,δji,δ*ji和正整數(shù)r>1,使得
為M矩陣,則模型(1)的周期解全局指數(shù)穩(wěn)定.在矩陣Σ中,
證明模型(1)可改寫為:
若令
其中r為正整數(shù),則由(H1)~(H3)和引理1可知
同理可得
令
設(shè)
則
由條件可知
也即
同理
所以
于是由定義1可知,模型(1)的周期解全局指數(shù)穩(wěn)定.】
考慮下列帶有時(shí)變時(shí)滯的BAM神經(jīng)網(wǎng)絡(luò)周期解的全局指數(shù)穩(wěn)定性:
(2)
是M矩陣,因此模型(2)的周期解全局指數(shù)穩(wěn)定.
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(責(zé)任編輯馬宇鴻)
An analysis on global exponential stability of periodic solutions for non-autonomous BAM neural networks with time-varying delays
WANG Ji-yu1,JIA Xiu-ling1,SHE Lian-bing2
(1.Department of Public Basic Education,Wanfang College of Science and Technology,Henan Polytechnic University, Zhengzhou 451400,Henna,China; 2.Department of Mathematics,Liupanshui Normal University,Liupanshui 553004,Guizhou,China)
Applying theM-matrix theory,Halanay inequality technique and some analysis techniques,some sufficient conditions are obtained for the global exponential stability of periodic solutions for non-autonomous BAM neural networks with time-varying delays.The results remove the assumptions of the boundedness,monotonicity or differentiability of the activation functions,and in some cases,the stability criteria can be easily checked.
BAM neural network;periodic solution;M-matrix;global exponential stability
10.16783/j.cnki.nwnuz.2016.05.003
2015-09-04;修改稿收到日期:2015-12-03
國家自然科學(xué)基金資助項(xiàng)目(11361074);河南省教育廳重點(diǎn)科研項(xiàng)目(15A110027);河南省基礎(chǔ)與前沿技術(shù)項(xiàng)目(142300410384)
王繼禹(1981—),男,河南南陽人,講師,碩士.主要研究方向?yàn)榉汉⒎址匠潭ㄐ岳碚?
E-mail:jywang1981@163.com
O 175.1
A
1001-988Ⅹ(2016)05-0010-04