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排序方式: 共有433条查询结果,搜索用时 359 毫秒
391.
392.
针对人脸识别中由于人脸表情、姿态、尺度、光照和其他环境参数变化而影响识别性能的问题,提出了一种随机优化算法。首先,将原始图像划分成特定空间子块,并使用二阶Volterra核寻找非线性函数映射;然后,使用人工蜂群算法获取最优Volterra核,从而在特征空间内最大化类间距离并最小化类内距离;最后,利用投票策略和最近邻分类器完成人脸的分类。在两个通用人脸数据集Yale A和扩展Yale B上对该算法进行了评估,并将其与其他统计学习算法和几种最新提出的方法进行了比较。实验结果表明了Levy变异人工蜂群算法优化Volterra核的有效性,识别效果明显优于许多现有算法。 相似文献
393.
394.
The nonlinear influence on system output spectrum is studied for a class of nonlinear systems which have Volterra series expansion. It is shown that under certain conditions the system output spectrum can be expressed in an alternating series with respect to some model parameters which define system nonlinearities. The magnitude of the system output spectrum can therefore be suppressed by exploiting the properties of alternating series. Sufficient (and necessary) conditions in which the output spectrum can be cast into an alternating series are studied. These results reveal a novel frequency-domain insight into the nonlinear influence on a system, and provide a new method for the analysis and design of nonlinear systems in the frequency domain. Examples are given to illustrate the results. 相似文献
395.
Li Huang Xian-Fang LiYulin Zhao Xiang-Yang Duan 《Computers & Mathematics with Applications》2011,62(3):1127-1134
In this paper, Taylor expansion approach is presented for solving (approximately) a class of linear fractional integro-differential equations including those of Fredholm and of Volterra types. By means of the mth-order Taylor expansion of the unknown function at an arbitrary point, the linear fractional integro-differential equation can be converted approximately to a system of equations for the unknown function itself and its m derivatives under initial conditions. This method gives a simple and closed form solution for a linear fractional integro-differential equation. In addition, illustrative examples are presented to demonstrate the efficiency and accuracy of the proposed method. 相似文献
396.
Nonlinear MPC based on a Volterra series model for greenhouse temperature control using natural ventilation 总被引:2,自引:0,他引:2
J.K. Gruber J.L. GuzmánF. Rodríguez C. BordonsM. Berenguel J.A. Sánchez 《Control Engineering Practice》2011,19(4):354-366
Suitable environmental conditions are a fundamental issue in greenhouse crop growth and can be achieved by advanced climate control strategies. In different climatic zones, natural ventilation is used to regulate both the greenhouse temperature and humidity. In mild climates, the greatest problem faced by far in greenhouse climate control is cooling, which, for dynamical reasons, leads to natural ventilation as a standard tool. This work addresses the design of a nonlinear model predictive control (NMPC) strategy for greenhouse temperature control using natural ventilation. The NMPC strategy is based on a second-order Volterra series model identified from experimental input/output data of a greenhouse. These models, representing the simple and logical extension of convolution models, can be used to approximate the nonlinear dynamic effect of the ventilation and other environmental conditions on the greenhouse temperature. The developed NMPC is applied to a greenhouse and the control performance of the proposed strategy will be illustrated by means of experimental results. 相似文献
397.
针对航空发动机的转速控制这个难题,提出了对非线性动态系统做建模研究的Volterra泛函方法的任意高阶核估计方法;该方法在核(kernel method)理论基础上,构造线性空间,将求解Volterra泛函各阶核的问题转化为求输出观测向量在希尔伯特空间(Hilbert space)子空间上的分量,利用线性空间中向量内积的求解而间接辨识出复杂的非线性动态系统;相对于其它在时域或频域估计Volterra核的理论,该方法数学基础牢固、计算量不随辨识精度增高而大量增加、理论上能够对任意高阶核进行估计,可对强非线性动态系统进行辨识。 相似文献
398.
本文在对Volterra泛函模型与ANN模型进行一致性研究的基础上,提出了基于Volterra泛函结构的神经网络水文模型(VNNH)。VNNH模型吸取了Volterra模型和ANN模型的优点,克服了它们的不足之处。VNNH模型设计了一种多项式的激活函数,克服了Volterra模型求解高阶核函数的困难。并利用自组织神经网络算法确定VNNH模型隐含层神经元的数目;根据Volterra模型的结构由流域的单位线确定VNNH模型的初始权值。将VNNH模型应用于两个实际流域的洪水模拟和预测中,取得了较为满意的结果。 相似文献
399.
基于沃尔特拉级数理论和多维拉普拉斯变换,给出了非线性逆系统的一种求解方法,得出了一些有意义的重要结果,并给出计算实例.借助于所给出的方法可以十分有效地解决数字信号处理、通信等技术中的非线性逆系统问题. 相似文献
400.
The identification of a special class of polynomial models is pursued in this paper. In particular a parameter estimation algorithm is developed for the identification of an input-output quadratic model excited by a zero mean white Gaussian input and with the output corrupted by additive measurement noise. Input-output crosscumulants up to the fifth order are employed and the identification problem of the unknown model parameters is reduced to the solution of successive triangular linear systems of equations that are solved at each step of the algorithm. Simulation studies are carried out and the proposed methodology is compared with two least squares type identification algorithms, the output error method and a combination of the instrumental variables and the output error approach. The proposed cumulant based algorithm and the output error method are tested with real data produced by a robotic manipulator. 相似文献