• The three-steps iterative algorithms converge strongly under suitable conditions.

    在适当的条件下,证明了三步迭代算法是强收敛的。

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  • They are stochastic search iterative algorithms and no demand of optimization object.

    它们均是随机搜索的迭代算法,对优化对象的初始状态无要求。

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  • There are many iterative algorithms for the solution of variational inequality and fixed point of mappings.

    我们考虑了这类变分不等式解的存在性及迭代逼近算法问题。

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  • The definition of Q rates of convergence in iterative algorithms is extened and the efficiency measure is developed.

    推广了迭代算法收敛分析中的Q 收敛阶的概念,据此给出了算法效率的一种一般的度量。

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  • The existing one-way hash functions without trapdoor are all iterative algorithms, for instance, MD and SHA family, etc.

    现有的无陷门单向散列函数都是迭代算法,例如SHA和MD系列算法等。

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  • All the major types of reconstruction approaches are discussed, including exact algorithms, approximate algorithms, and iterative algorithms.

    文中涉及各种主要重建算,法包括准确重建,近似重建和迭代重建算法。

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  • Based on the iterative least squares principle, two least-squares-iterative algorithms are developed for CARMA models and output error models.

    基于迭代最小二乘原理,提出了辨识CARMA模型和输出误差模型参数的最小迭代算法。

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  • The iterative algorithms in C language were given, which used direct data replacement to reduce the dimension of matrix and saved the storage space.

    在迭代算法中,采用直接数据置换降低矩阵维数,节省了存储空间,提高了运算速度。

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  • Iterative algorithms typically consist of several different loops performing different aspects of the process, and thus introduce their own performance issues.

    迭代算法通常包括几个不同的循环,分别对应算法过程的不同方面,也会导致自己的性能为题。

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  • This thesis includes three chapters, which mainly discusses the iterative algorithms for solving nonlinear equations problems and nonlinear variational inequality problems.

    本文主要讨论求解非线性方程组问题与变分不等式问题的迭代算法。全文共分三章。

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  • A new iterative algorithms to approximate the solution of the class of nonlinear implicit quasi variational inclusions in Banach space is constructed using resolvent operator.

    利用预解式算子技巧构造了一类求变分包含逼近解的迭代算法,并讨论了由此算法产生的迭代序列的收敛性。

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  • Based upon texture feature and whole interrelation of, pixels in local region, an iterative algorithms of approximation to known pixels was performed to restore the damaged data.

    基于局部域上象元的整体相关性和基图象纹理连续性,对已知象元进行迭代拟合,同时修复多点缺损数据。

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  • Extracting surface depth from a shaded image (SFS) is one of the classic problems in computer vision. Many iterative algorithms correspond to a feasible surface, but converge slowly.

    从单幅图像获得物体的表面高度是计算机视觉中的一个重要研究领域,迭代算法的计算精确度高,但收敛速度较慢。

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  • As the calculation speed of the CPU is fast developed, more consideration is paid to the iterative algorithms in tomographic reconstruction, which were only experimented as a research method before.

    随着计算机运算速度的飞速发展,以前只是被看成一种研究方法的迭代算法在图像重建中越来越引起人们的重视,并且已经在科研、工业和医学领域中得到了实际应用。

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  • The contributive equation of discontinuous interface to the system of equations is derived and nonlinear iterative algorithms for simulating the contact state of a discontinuous interface are studied.

    为此,推导了不连续面对整体平衡方程组的贡献方程,研究了模拟不连续面实际接触状态的非线性迭代算法。

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  • The parameters include generator polynomial of component codes, interleave length and the type of interleavers, iterative decoding algorithms and iteration number, code rates and channel models et al.

    这些参数主要包括分量码、交织长度和交织器类型、迭代译码算法和译码迭代次数、编码速率以及信道条件等。

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  • In the paper, based on the image registration, iterative back-projection technique is used to construct high resolution from image sequences, in which algorithms and realization are given in detail.

    文章在图像配准的基础之上,采用后向投影迭代算法对图像序列进行了高分辨率重构,并给出了其中详细的算法和实现过程。

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  • Using this equivalence, we construct some new perturbed proximal point algorithms and prove the convergence of iterative sequences generated by the algorithms.

    利用这种等价性,构造了一些新的扰动近似点算法,并证明了由此算法所产生的迭代序列的收敛性。

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  • Cyclic Bayesian network provides modeling method and inference algorithms for the management of software project iterative process risk.

    有环贝叶斯网络的研究,为管理软件项目迭代过程风险提供了建模方法和模型求解算法。

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  • Chapter 3 studies and analyzes the wavelet-based image restoration algorithms, including threshold deconvolution algorithm, iterative regularization algorithm and parameter model algorithm.

    第3章研究和分析了基于小波的图像复原算法,包括小波域的阈值反卷积算法、迭代正则化算法和参数模型算法。

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  • To further improve the calibration precision of the previous regression algorithms, an iterative local algorithm of color calibration based on kernel partial least squares regression is proposed.

    为进一步提高回归算法的色彩校正精度,提出一个基于核偏最小二乘回归的局部迭代算法。

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  • Designs of the iterative learning algorithms, the most important problems in the ILC, are also studied in this dissertation.

    迭代学习算法设计一直是迭代学习控制研究的重点,本文从一些新的视角做了探讨。

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  • Their common purpose is to compute the displacement at each iteration step in any optimization algorithms and obtain a new iteration point. But the methods of produce iterative step are different.

    它们的共同目的都是在优化算法中求出每次迭代步的位移,从而求出新的迭代点,但是它们产生迭代步位移的途径不同。

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  • Two prototype algorithms of iterative learning identification, iterative learning Bayes and stochastic Newton algorithms, are proposed with detail.

    推导得到两种迭代学习辨识算法:迭代学习贝叶斯法和迭代学习随机牛顿法。

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  • And compared with traditional vertical projection algorithms, the novel simultaneous parallel projection can greatly accelerate the iterative process without losses of accuracy.

    与传统的垂直投影算法相比,新算法能在保证重建准确度的前提下大幅度的提高收敛速度。

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  • The characteristics of two main parallel computing algorithms on solving large sparse linear system equation-direct method and iterative method will be analyzed and summarized in this paper.

    本文全面总结了当前并行求解大型稀疏线性方程组的两种主要方法—直接法和迭代法。

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  • It is shown that, if algorithms for performing the QR decomposition are free from calculation of square root, the related iterative refinement algorithms can also be square root free.

    证明了:若用QR分解所作的算法无需计算平方根,则相应的迭代加细算法也无需计算平方根。

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  • These algorithms are aimed at reducing the number of repeated iterative operations. The use of radix 4 leads to 2-digit results for each iterative operations.

    基本出发点是减少运算的重复迭代次数,采用每次运算能得到二位结果的算法而不是常规的每次只能得到一位结果的二进制算法。

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  • The new algorithm is different from the algorithms of iterative learning control proposed recently, and is with nonlinear structure.

    这类新算法与目前所有迭代学习控制算法不同,具有非线性结构。

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  • The new algorithm is different from the algorithms of iterative learning control proposed recently, and is with nonlinear structure.

    这类新算法与目前所有迭代学习控制算法不同,具有非线性结构。

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