解循环三对角线性方程组的追赶法

循环三对角、循环 Toeplitz三对角线性方程组的求解在科学与工程计算中有着广泛的应用 .运用矩阵分解给出此类方程组的直接解法 ;通过分析其特性 ,给出了达到机器精度的截断算法 ,其计算复杂度几乎等同于求解一个三对角线性方程组的计算复杂度 .数值实验的结果与理论分析的结果十分吻合 .该算法还推广到求解拟三对角线性方程组 .     

基于混合遗传算法求解非线性方程组

将非线性方程组的求解问题转化为函数优化问题，且综合考虑了拟牛顿法和遗传算法各自的优点，提出了一种用于求解非线性方程组的混合遗传算法。该混合算法充分发挥了拟牛顿法的局部搜索、收敛速度快和遗传算法的群体搜索、全局收敛的优点。为了证明该混合遗传算法的有效性，选择了几个典型的非线性方程组，从实验计算结果、收敛可靠性指标对比不同算法进行分析。数值模拟实验表明，该混合遗传算法具有很高的精确性和收敛性，是求解非线性方程组的一种有效算法。     

近似三对角Toeplitz方程组的快速分布式并行算法

利用近似三对角Toeplitz矩阵的特殊结构，提出了一种新的求解近似三对角Toeplitz方程组的快速算法．在三对角Toeplitz矩阵的近似LU分解的基础上，利用“分而治之”的思想，并结合秦九韶技术和特殊的数学技巧减少大量的冗余计算，提出了求解近似Toeplitz三对角方程组的快速分布式并行算法，并在理论上证明了算法具有近似于线性的加速比．最后通过数值实验证明，新的并行算法具有较高的并行效率，并且当矩阵阶数n足够大时，算法的加速比趋近于线性加速比．     

关于Vandermonde矩阵的串行与并行复杂性

为n+1阶Vandermonde矩阵,简称V阵。 本文首先给出求解相应线性代数方程组(简称V型方程组)的递推算法。算术运算总次数为O(n~2)级,接着进一步利用快速插值算法导出求V阵逆的O(n~2)算法,并分析了这两种算法的并行时间复杂性。     

拟牛顿法求解化工过程数学模型

使用不需求取偏导数的拟牛顿法,求解化工过程模拟中产生的非线性方程组形式的数学模型。当未知数各分量间绝对值相差较大时,提出了改善收敛性的几种方法,即：（1）加入阻尼因子,以减少迭代值的震荡、（2）将方程适当降价;（3）将差商的绝对步长改为相对步长;（4）新迭代值超来其物理意义范围时,强制其回至其初始值。计算结果表明,与牛顿－拉夫森法相比,拟牛顿法不需求偏导数,对初值要求低,较雅可比迭代法收敛速度快,可用于求解化工过程的非线性方程组。     

粒子群算法在求解方程组中的应用

提出了采用粒子群算法求解线性方程组和非线性方程组的智能算法。采用粒子群算法求解方程组具有形式简单、收敛迅速和容易理解等特点,且能在一次计算中多次发现方程组的解,可以解决非线性方程组多解的求解问题,为线性方程组和非线性方程组的求解提供了一种新的方法。     

一种求解非线性方程组的量子粒子群算法

针对传统非线性方程组的解法对初始值敏感、收敛性差等问题,提出一种求解非线性方程组的量子粒子群算法.用量子位的概率幅对粒子位置编码,通过量子旋转门和量子非门完成粒子的更新与变异.该算法可发挥量子粒子群的群体搜索能力和全局收敛性,在算法中融入拟牛顿法,加强局部搜索能力,提高求解精度.数值模拟实验表明,算法有着可靠的收敛性和较高的收敛速度与精度.     

基于混合遗传算法求解非线性方程组

将非线性方程组的求解问题转化为函数优化问题,且综合考虑了拟牛顿法和遗传算法各自的优点,提出了一种用于求解非线性方程组的混合遗传算法。该混合算法充分发挥了拟牛顿法的局部搜索、收敛速度快和遗传算法的群体搜索、全局收敛的优点。为了证明该混合遗传算法的有效性,选择了几个典型的非线性方程组,从实验计算结果、收敛可靠性指标对比不同算法进行分析。数值模拟实验表明,该混合遗传算法具有很高的精确性和收敛性,是求解非线性方程组的一种有效算法。     

Toeplitz矩阵相乘的一种新快速算法

将Toeplitz矩阵分解为一个循环矩阵和一个下三角Toeplitz矩阵之和,以及一般卷积向循环卷积的转化,借助快速Fouier变换(FFT),导出了一种计算两个n阶Toeplitz矩阵乘积的新快速算法,其算法复杂性为2n2 63/4n log2n-15n-34次实乘运算,4n2 63/2n log2n-18n 23次实加运算,与已有的优化算法相比,在实乘次数有所降低的同时,实加次数降低了近1/3,是目前复杂性最小的一种算法.     

非线性方程组求解的一种新方法

针对现有的非线性方程组求解方法不能同时收敛到所有解的问题,提出了一种混合小生境遗传算法的求解新方法.采用确定性拥挤小生境创造出种群的小生境进化环境,克服遗传算法的遗传漂移现象,维持种群的多样性,使算法能同时收敛到多个解;以拟牛顿算法作为遗传算法的局部搜索算子进行精确搜索,进一步提高算法收敛速度和精度.选择了几组典型的多解非线性方程组进行了求解验证,结果表明所设计的混合小生境遗传算法能在解的定义域内同时收敛到所有解,收敛速度快、精度高,是求解非线性方程组全局解的一种有效方法.     

一个反求Bezier曲面控制点的算法

本文将反求m×n次Bezier曲面控制点问题,转化为求解m+1个n+1阶线性方程组和n+1个m+1阶线性方程组问题。这些线性方程组的系数矩阵是著名的Vandermonde矩阵。通过求解Vandermonde矩阵的逆矩阵,使CAD/CAM曲面造型中常常遇到的反求Bezier曲面控制点问题得到有效的解决。同时本文给出了一种求解Vandermonde矩阵的逆矩阵的方法。     

Numerical solution of a fuzzy system of linear equations with polynomial parametric form

A systems of linear equations are used in many fields of science and industry, such as control theory and image processing, and solving a fuzzy linear system of equations is now a necessity. In this work we try to solve a fuzzy system of linear equations having fuzzy coefficients and crisp variables using a polynomial parametric form of fuzzy numbers.     

Generalized newton multi-step iterative methods GMNp,m for solving system of nonlinear equations

A generalization of the Newton multi-step iterative method is presented, in the form of distinct families of methods depending on proper parameters. The proposed generalization of the Newton multi-step consists of two parts, namely the base method and the multi-step part. The multi-step part requires a single evaluation of function per step. During the multi-step phase, we have to solve systems of linear equations whose coefficient matrix is the Jacobian evaluated at the initial guess. The direct inversion of the Jacobian it is an expensive operation, and hence, for moderately large systems, the lower-upper triangular factorization (LU) is a reasonable choice. Once we have the LU factors of the Jacobian, starting from the base method, we only solve systems of lower and upper triangular matrices that are in fact computationally economical. The developed families involve unknown parameters, and we are interested in setting them with the goal of maximizing the convergence order of the global method. Few families are investigated in some detail. The validity and numerical accuracy of the solution of the system of nonlinear equations are presented via numerical simulations, also involving examples coming from standard approximations of ordinary differential and partial differential nonlinear equations. The obtained results show the efficiency of constructed iterative methods, under the assumption of smoothness of the nonlinear function.     

Solving fuzzy equations using evolutionary algorithms and neural nets

 In this paper we use evolutionary algorithms and neural nets to solve fuzzy equations. In Part I we: (1) first introduce our three solution methods for solving the fuzzy linear equation AˉXˉ + Bˉ= Cˉ; for Xˉ and (2) then survey the results for the fuzzy quadratic equations, fuzzy differential equations, fuzzy difference equations, fuzzy partial differential equations, systems of fuzzy linear equations, and fuzzy integral equations; and (3) apply an evolutionary algorithm to construct one of the solution types for the fuzzy eigenvalue problem. In Part II we: (1) first discuss how to design and train a neural net to solve AˉXˉ + Bˉ= Cˉ for Xˉ and (2) then survey the results for systems of fuzzy linear equations and the fuzzy quadratic.     

An iteration‐based hybrid parallel algorithm for tridiagonal systems of equations on multi‐core architectures

An optimized parallel algorithm is proposed to solve the problem occurred in the process of complicated backward substitution of cyclic reduction during solving tridiagonal linear systems. Adopting a hybrid parallel model, this algorithm combines the cyclic reduction method and the partition method. This hybrid algorithm has simple backward substitution on parallel computers comparing with the cyclic reduction method. In this paper, the operation count and execution time are obtained to evaluate and make comparison for these methods. On the basis of results of these measured parameters, the hybrid algorithm using the hybrid approach with a multi‐threading implementation achieves better efficiency than the other parallel methods, that is, the cyclic reduction and the partition methods. In particular, the approach involved in this paper has the least scalar operation count and the shortest execution time on a multi‐core computer when the size of equations meets some dimension threshold. The hybrid parallel algorithm improves the performance of the cyclic reduction and partition methods by 19.2% and 13.2%, respectively. In addition, by comparing the single‐iteration and multi‐iteration hybrid parallel algorithms, it is found that increasing iteration steps of the cyclic reduction method does not affect the performance of the hybrid parallel algorithm very much. Copyright © 2015 John Wiley & Sons, Ltd.     

Computation of Determinants, Adjoint Matrices, and Characteristic Polynomials without Division

Algorithms are proposed for computing the characteristic polynomial, determinant, and adjoint matrix for a n × n matrix and for solving a system of n-1 linear homogeneous equations in n variables by Cramer's rule using O(n ⁴ ) ring operations (without the division operation) over an arbitrary commutative ring. The exponent in the estimate of the computation time can be additionally reduced if an algorithm of asymptotically fast matrix multiplication is used.     

圆圈结构及其变化系统的PageRank排名研究

研究了Google中的网页级别技术的PageRank算法。不同于通常的做法,通过求解一个线性方程组得到网页的非标准化的PageRank值。利用这个非标准化的PageRank值,其将主要考查圆圈结构及其变化系统。将找到这些系统中标准化的和非标准化的PageRank值表达式。最终研究了当系统结点数或参数发生一些改变时PageRank值的变化情况。     

基于同态加密的线性系统求解方案

在科学计算、统计分析以及机器学习领域,许多实际问题都可以归结到线性系统Ax=b的求解,如最小二乘估计和机器学习中的回归分析等.而实际中用于计算的数据往往由不同用户拥有且包含用户的敏感信息.当不同的数据拥有者想在合作求解一个模型的同时保护数据的隐私,同态加密可以作为解决方法之一.针对两个用户参与的场景,基于Cheon等提...     

Taylor polynomial solutions of systems of linear differential equations with variable coefficients

A Taylor collocation method has been presented for numerically solving systems of high-order linear ordinary, differential equations with variable coefficients. Using the Taylor collocation points, this method transforms the ODE system and the given conditions to matrix equations with unknown Taylor coefficients. By means of the obtained matrix equation, a new system of equations corresponding to the system of linear algebraic equations is gained. Hence by finding the Taylor coefficients, the Taylor polynomial approach is obtained. Also, the method can be used for the linear systems in the normal form. To illustrate the pertinent features of the method, examples are presented and results are compared.