• 제목/요약/키워드: Cellular neural networks

검색결과 61건 처리시간 0.038초

DELAY-DEPENDENT GLOBAL ASYMPTOTIC STABILITY ANALYSIS OF DELAYED CELLULAR NEURAL NETWORKS

  • Yang, Yitao;Zhang, Yuejin
    • Journal of applied mathematics & informatics
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    • 제28권3_4호
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    • pp.583-596
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    • 2010
  • In this paper, the problem of delay-dependent stability analysis for cellular neural networks systems with time-varying delays was considered. By using a new Lyapunov-Krasovskii function, delay-dependant stability conditions of the delayed cellular neural networks systems are proposed in terms of linear matrix inequalities (LMIs). Examples are provided to demonstrate the reduced conservatism of the proposed stability results.

GLOBAL EXPONENTIAL STABILITY OF BAM FUZZY CELLULAR NEURAL NETWORKS WITH DISTRIBUTED DELAYS AND IMPULSES

  • Li, Kelin;Zhang, Liping
    • Journal of applied mathematics & informatics
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    • 제29권1_2호
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    • pp.211-225
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    • 2011
  • In this paper, a class of bi-directional associative memory (BAM) fuzzy cellular neural networks with distributed delays and impulses is formulated and investigated. By employing an integro-differential inequality with impulsive initial conditions and the topological degree theory, some sufficient conditions ensuring the existence and global exponential stability of equilibrium point for impulsive BAM fuzzy cellular neural networks with distributed delays are obtained. In particular, the estimate of the exponential convergence rate is also provided, which depends on the delay kernel functions and system parameters. It is believed that these results are significant and useful for the design and applications of BAM fuzzy cellular neural networks. An example is given to show the effectiveness of the results obtained here.

ON STEPANOV WEIGHTED PSEUDO ALMOST AUTOMORPHIC SOLUTIONS OF NEURAL NETWORKS

  • Lee, Hyun Mork
    • Korean Journal of Mathematics
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    • 제30권3호
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    • pp.491-502
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    • 2022
  • In this paper we investigate some sufficient conditions to guarantee the existence and uniqueness of Stepanov-like weighted pseudo almost periodic solutions of cellular neural networks on Clifford algebra for non-automomous cellular neural networks with multi-proportional delays. Our analysis is based on the differential inequality techniques and the Banach contraction mapping principle.

EXISTENCE AND EXPONENTIAL STABILITY OF ALMOST PERIODIC SOLUTIONS FOR CELLULAR NEURAL NETWORKS WITH CONTINUOUSLY DISTRIBUTED DELAYS

  • Liu Bingwen;Huang Lihong
    • 대한수학회지
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    • 제43권2호
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    • pp.445-459
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    • 2006
  • In this paper cellular neural networks with continuously distributed delays are considered. Sufficient conditions for the existence and exponential stability of the almost periodic solutions are established by using fixed point theorem, Lyapunov functional method and differential inequality technique. The results of this paper are new and they complement previously known results.

STABILITY OF IMPULSIVE CELLULAR NEURAL NETWORKS WITH TIME-VARYING DELAYS

  • Zhang, Lijuan;Yu, Lixin
    • Journal of applied mathematics & informatics
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    • 제29권5_6호
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    • pp.1327-1335
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    • 2011
  • This paper demonstrates that there is a unique exponentially stable equilibrium state of a class of impulsive cellular neural network with delays. The analysis exploits M-matrix theory and generalized comparison principle to derive some easily verifiable sufficient conditions for the global exponential stability of the equilibrium state. The results extend and improve earlier publications. An example with its simulation is given for illustration of theoretical results.

EXISTENCE AND EXPONENTIAL STABILITY OF ALMOST PERIODIC SOLUTIONS FOR CELLULAR NEURAL NETWORKS WITHOUT GLOBAL LIPSCHITZ CONDITIONS

  • Liu, Bingwan
    • 대한수학회지
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    • 제44권4호
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    • pp.873-887
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    • 2007
  • In this paper cellular neutral networks with time-varying delays and continuously distributed delays are considered. Without assuming the global Lipschitz conditions of activation functions, some sufficient conditions for the existence and exponential stability of the almost periodic solutions are established by using the fixed point theorem and differential inequality techniques. The results of this paper are new and complement previously known results.

Cellular Neural Network을 이용한 숫자인식에 관한 연구 (A Study on the Number Recognition using Cellular Neural Network)

  • 전흥우;김명관;정금섭
    • 한국정보통신학회논문지
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    • 제6권6호
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    • pp.819-826
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    • 2002
  • 셀룰러 뉴럴 네트워크는 국부적 연결특성을 가지고 있어 실시간 이미지처리에 적합한 뉴럴 네크워크이다. 또한 국부적 연결특징은 VLSI구현에 적합하다. 그의 응용분야는 패턴인식과 숫자인식 및 영상처리에 응용되고 있다. 본 논문에서, CNN은 전처리 단계로서 숫자의 특징점 추출에 이용된다. CNN을 이용한 그림자검출은 4내지 6방향으로 검출하여 숫자의 특징점을 방향별로 추출한다. 분류단계에서 이러한 형상자료는 다층BP뉴럴 네트워크의 입력벡터에 적합하도록 압축되어 입력된다. 실험결과 CNN을 통한 숫자인식은 굴림체의 경우96%이상의 인식율을 보여 만족할 만한 결과를 얻었다.

EXISTENCE AND EXPONENTIAL STABILITY OF ALMOST PERIODIC SOLUTION FOR SHUNTING INHIBITORY CELLULAR NEURAL NETWORKS WITH DISTRIBUTED DELAYS AND LARGE IMPULSES

  • Zuo, Yi;Wang, Yaonan;Huang, Lihong;Li, Chunsheng
    • 대한수학회지
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    • 제46권5호
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    • pp.1071-1085
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    • 2009
  • This paper considers the problem of existence and exponential stability of almost periodic solution for shunting inhibitory cellular neural networks with distributed delays and large impulses. Based on the contraction principle and Gronwall-Bellman's inequality, some sufficient conditions are obtained. The results of this paper are new and they complement previously known results.

A Study and Implementation on Automatic Design of Artificial Neural Networks using Cellular Automa Techniques

  • Sim, Kwee-Bo;Lee, Dong-Wook;Ban, Chang-Bong;Kwak, Sang-Young
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 2001년도 ICCAS
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    • pp.115.2-115
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    • 2001
  • This paper is the result of constructing information processing system such as living creatures´ brain based on artificial life techniques. The living things are best information processing system in themselves. One individual is developed from a generative cell. And a species of this individual has adapted itself to the environment through evolution. We present a new type of neural architecture consistiong of chaotic neurons and implementation. To evolve chaotic neural systems, we use cellular automata. In order to obtain the best neural networks in the environment, we evolve the arrangement of initial cells. The cell, that is neuron of neural networks, is modeled on chaotic ...

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셀룰라 오토마타 기반 신경 회로망의 진화를 위한 전략 (Strategies for Evolution in Neural Networks based on Cellular Automata)

  • 조용군;이원희;강훈
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 1998년도 하계학술대회 논문집 G
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    • pp.2193-2196
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    • 1998
  • Cellular automata are dynamical systems in which space and time are discrete, where each cell has a finite number of states and updates its states by interactive rules among the cell-neighborhood. From the characteristics of self-reproduction and self- organization, it is possible to create a neural network which has the specific patterns or structures dynamically. CAM-Brain is a kind of such neural network system which evolves its structure by adopting evolutionary computations like genetic algorithms (GA). In this paper, we suggest the evolution strategies for the structure of neural networks based on cellular automata.

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