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Thus, we must recur to some prior models and high effective approximative method to solve complex modelling and computing.

我们必须借助于一些先验模型、高效的逼近算法才能解决复杂的建模与计算问题。

The results show their asymptotical agreement with the theoretical bound and the advantageous RPUKY performance.

结果表明,两种次优算法的曲线逐渐逼近理论下界,且PRUKF性能更优。

Firstly, the definition of image representation, measure of sparsity, and the basic methods of sparse representation are reviewed. And then, we analyze the performance of nonlinear approximation of Ridgelet, Curvelet, Contourlet and Bandelet transform.

论文阐述了信号表示的定义、稀疏性度量以及图像稀疏表示的基本理论方法,分析与比较了脊波变换、曲线波变换、Contourlet变换、Bandelet变换各自的非线性逼近性能。

Then as for an arbitrary initializing bisymmetric matrix, we just need to get the bisymmetric solutions of the new equation in finite steps by applying the iterative method.

并将求最佳逼近的问题转化为求一个新方程的极小范数解的问题,同样可用迭代法求解。

In this paper, we first introduce the concepts and structures of generalized per-symmetric matrix, generalized centro-symmetric matrix or generalized bisymmetric matrix.

本文介绍了广义广对称矩阵、广义中心对称矩阵以及广义双对称矩阵的概念及结构,研究了这些特殊矩阵集合中,矩阵方程AXB=C及矩阵方程组A_1XB_1=C_1,A_2XB_2=C_2的迭代解法,同时考虑了相应的最佳逼近问题。

Furthermore,the optimal approximation bisymmetric solution pair to a given bisymmetric matrix pair in Frobenius norm can be obtained by finding the least norm bisymmetric solution pair of new matrix equation ,where .

另外,给定双对称矩阵对,通过求矩阵方程的双对称解对,得到它的最佳逼近双对称解对。

Iterative method; Generalized bisymmetric solution; Least-norm solution; Optimal approximation

迭代解法;广义双对称解;极小范数解;最佳逼近

In addition, the unique optimal approximation solution $\\\\\\\\\\\\\\\\hat X$ to given matrix $X_0 $ in Frobenius norm can be derived by finding the least-norm generalized bisymmetric solution $\\\\\\\\\\\\\\\\widetilde X^\\\\\\\\\\\\\\\\ast$ of the new matrix equation $A\\\\\\\\\\\\\\\\widetilde X B=\\\\\\\\\\\\\\\\widetilde C$, here,$\\\\\\\\\\\\\\\\widetilde X=X-X_0$, and $\\\\\\\\\\\\\\\\widetilde C=C-AX_0B$.

另外,对于给定矩阵X_0的最佳逼近解$\\\\\\\\\\\\\\\\hat X$,可以通过求解新的矩阵方程$A\\\\\\\\\\\\\\\\widetilde X B=\\\\\\\\\\\\\\\\widetilde C$得到,其中$\\\\\\\\\\\\\\\\widetilde X=X-X_0$,$\\\\\\\\\\\\\\\\widetilde C=C-AX_0B$。

A robust output feedback controller is advanced by using the DRNN-based observer presented above, so that the output-matching and lipschitz conditions are not imposed on the uncertainties; Robust adaptive controller is used in a class of nonlinear systems based on neural networks and H〓 methods, thereby the constraint on uncertainties with largest known boundness is removed, not as in H〓 methods.

利用本文的动态神经网络鲁棒观测器,设计了鲁棒输出反馈控制器,取消了已有结果对未知动态的输出匹配条件的限制;结合静态神经网和H〓控制方法,对一类非线性系统设计了鲁棒自适应反馈控制器,克服了H〓控制要求不确定性最大可能界已知的不足,其最大优点是仅要求网络逼近误差有界,且不要求网络权的离线训练。

Applying the conjugate gradient method, an iterative algorithm is presented to solve the constrained matrix equation AXB+CXD=F over centrosymmetric matrix X and its optimal approximation.

应用共轭梯度思想,给出了求解约束矩阵方程AXB+CXD=F的中心对称解及其最佳逼近的迭代算法。

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