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模糊ART神经网络在运动目标识别中的应用 总被引:1,自引:0,他引:1
本文在讨论模糊ART神经网络及其算法的基础上,研究和提出了一种三维运动目标识别方法,利用模糊ART神经网络对运动目标的目标侧面图形进行学习和模式识别。模拟实验表明了该方法的有效性。 相似文献
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故障诊断中模糊神经网络的应用研究 总被引:1,自引:0,他引:1
文章给出了利用模糊神经网络诊断故障的数学模型、基本原理、方法、步骤 ,和模糊网络的学习流程 ,并利用梯度法推导出两种诊断算法 ;在对某发动机滑油典型故障样本的仿真过程中 ,结果完全正确 ,对非样本故障的仿真 ,准确率达 90 % . 相似文献
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模糊神经网络的一种混合递推学习算法 总被引:4,自引:1,他引:3
提出一种新型混合递推学习算法,记为FNRPCL 及FNIGLS,这种算法用来调整模糊神经网络中隶属函数的中心和宽度,以及输出层的连接权值 相似文献
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The measure of uncertainty is adopted as a measure of information. The measures of fuzziness are known as fuzzy information measures. The measure of a quantity of fuzzy information gained from a fuzzy set or fuzzy system is known as fuzzy entropy. Fuzzy entropy has been focused and studied by many researchers in various fields. In this paper, firstly, the axiomatic definition of fuzzy entropy is discussed. Then, neural networks model of fuzzy entropy is proposed, based on the computing capability of neural networks. In the end, two examples are discussed to show the efficiency of the model. 相似文献
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小卫星高性能,高自主的发展趋势对于在轨故障诊断技术的实现要求日益迫切,而受小卫星体积小,重量轻,能源少的限制,当前常用的建立在高性能计算机硬件基础上的各种诊断方法不再适用于强调实时性,准确性的在轨运行监测,诊断与恢复和重构重处理。本文小卫星一体化系统总体设计技术研究与集成化设计系统为基础,采用一种神经网络与模糊系统相结合的模糊神经网络(FNN)模型来分区域表示诊断系统并基于该FNN模型进行诊断推量 相似文献
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模糊粗糙集理论研究进展 总被引:18,自引:3,他引:18
介绍模糊粗糙集的概念及发展进程.提出了理论建立过程中,分别以推广到模糊集、引入模糊逻辑算子、拓展到两个论域为特点的三个发展阶段;分析、比较了各阶段代表性理论的特点,并对模糊粗糙集的未来发展作出了预期。 相似文献
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在取消了神经元之间的连接权系数对称限制的基础上 ,讨论了 Hopfield神经网络的稳定性 ,得到了一些有益结论 .并将其应用于 Hopfield神经网络算法的改进上 .进而依据改进的算法以有价证券的选择为例进行了随机模拟 ,取得了令人满意的结果 . 相似文献
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研究多维Cardaliguet-Eurrard型神经网络算子的逼近问题.分别给出该神经网络算子逼近连续函数与可导函数的速度估计,建立了Jackson型不等式. 相似文献
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Stavros J. Perantonis Nikolaos Ampazis Vassilis Virvilis 《Annals of Operations Research》2000,99(1-4):385-401
Conventional supervised learning in neural networks is carried out by performing unconstrained minimization of a suitably defined cost function. This approach has certain drawbacks, which can be overcome by incorporating additional knowledge in the training formalism. In this paper, two types of such additional knowledge are examined: Network specific knowledge (associated with the neural network irrespectively of the problem whose solution is sought) or problem specific knowledge (which helps to solve a specific learning task). A constrained optimization framework is introduced for incorporating these types of knowledge into the learning formalism. We present three examples of improvement in the learning behaviour of neural networks using additional knowledge in the context of our constrained optimization framework. The two network specific examples are designed to improve convergence and learning speed in the broad class of feedforward networks, while the third problem specific example is related to the efficient factorization of 2-D polynomials using suitably constructed sigma-pi networks. 相似文献
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本文旨在研究一类带变时滞的随机模糊细胞神经网络的稳定性.通过构造恰当的Lyapunov泛函并运用线性矩阵不等式(LMI)理论,作者给出了保证这类神经网络全局渐近稳定的充分条件.本文推导出两个定理:一个用以判定文中模型的全局渐进稳定性,一个用以判定该模型在均方意义下的全局渐近稳定性. 相似文献
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Exponential Stability of Positive Conformable BAM Neural Networks with Communication Delays 下载免费PDF全文
In this paper, we consider a class of nonlinear differential equations with delays described by conformable fractional derivative. This type of differential equations can be used to describe dynamics of various practical models including biological and artificial neural networks with heterogeneous time-varying delays. By novel comparison techniques via fractional differential and integral inequalities, we prove under assumptions involving the order-preserving property of nonlinear vector fields that, with nonnegative initial states and inputs, the system state trajectories are always nonnegative for all time. This feature, called positivity, induces a special character, namely the monotonicity of the system. We then derive tractable conditions in terms of linear programming and prove, by utilizing the Brouwer''s fixed point theorem and comparisons induced by the monotonicity, that the system possesses a unique positive equilibrium point which attracts exponentially all state trajectories. An application to the exponential stability of fractional linear time-delay systems is also discussed. Numerical examples with simulations are given to illustrate the theoretical results. 相似文献
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神经网络平衡点存在唯一的充要条件 总被引:1,自引:0,他引:1
针对一类广泛的激活函数 ,利用矩阵理论 ,建立了相应的Hopfield神经网络平衡点存在唯一的充要条件 .同时 ,也给出相应的离散神经网络平衡点存在唯一的充要条件 .比较现有的文献 ,本文的结果适用范围更为广泛 相似文献