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kalman_filter
- OPTIONAL INPUTS (string/value pairs [default in brackets]) model - model(t)=m means use params from model m at time t [ones(1,T) ] In this case, all the above matrices take an additional final dimension, i.e., A(:,:,m), C(:,:,m), Q(:,:,m), R
cgls
- 用于解反问题的共轭梯度法,对于Ax=b,输入矩阵A,列向量b,以及迭代步数k,可求的列向量x-Solution of inverse problems for the conjugate gradient method, for Ax = b, the input matrix A, the column vector b, as well as the number of iterations k, rectifiable column vector x
mr2
- 用于解反问题的算法,对于Ax=b,输入矩阵A,列向量b,以及迭代步数k,可求的列向量x-The algorithm for solution of the inverse problem, for Ax = b, the input matrix A, the column vector b, as well as the number of iterations k, rectifiable column vector x
nu
- 用于解反问题的算法,对于Ax=b,输入矩阵A,列向量b,以及迭代步数k,可求的列向量x-The algorithm for solution of the inverse problem, for Ax = b, the input matrix A, the column vector b, as well as the number of iterations k, rectifiable column vector x
LSQR
- 采用CG法求解稀疏不对称的Ax=b-Implementation of a conjugate-gradient type method for solving sparse linear equations and sparse least-squares problems: Solve Ax = b or minimize || Ax- b ||2 or minimize || Ax- b ||2+ d2 ||x||2. The matrix A may be squ
MINRES
- 采用CG法求解稀疏对称奇异矩阵得到的Ax=b-Implementation of a conjugate-gradient type method for solving sparse linear equations: Solve Ax = b or (A- sI)x = b. The matrix A- sI must be symmetric but it may be definite or indefinite or singular. The scalar s is a
SYMMLQ
- 采用CG法求解稀疏对称非奇异矩阵得到的线性系统Ax=b-Implementation of a conjugate-gradient type method for solving sparse linear equations: Solve Ax = b or (A- sI)x = b. The matrix A- sI must be symmetric and nonsingular, but it may be definite or indefinite. The scal
BRMUL
- 求m*n阶矩阵A与n*k阶矩阵B的乘积矩阵C=AB-we can get the product matrix C from m*n matrix A and n*k matrix B.
BCMUL
- 求m*n阶复矩阵A与n*k阶复矩阵B的乘积矩阵C=AB。-we can get product matrix C from m*n complex matrix A and n*k complex matrix B.
single
- 一般性的奇异值分解算法,float浮点型。-SGGSVD computes the generalized singular value decomposition (GSVD) * of an M-by-N real matrix A and P-by-N real matrix B: * * U*A*Q = D1*( 0 R ), V*B*Q = D2*( 0 R ) * * where U, V and Q are orthogonal matric
single
- 使用奇异值分解来帮助求解最小二乘问题,特别是在方程系数矩阵不满秩的情况下。-SGELSD computes the minimum-norm solution to a real linear least * squares problem: * minimize 2-norm(| b- A*x |) * using the singular value decomposition (SVD) of A. A is an M-by-N * matrix which
dianziping
- 电子屏字符显示器 * * "电子设计" * * 2001.10.23 * ************************* 四个显示字符数据表放在50H-6FH单元内,字符用8*8点阵,R4(30H)用于 控制显示静止字的时间,R5(31H)静止字显示跳转地址步距,B内放显示首址-E-screen character display* * " electronic design" * * 2001.10.23* ******************
adc3
- take a input vector which is no of users of b[kx1] and code vector which will be a matrix now s=[Nxk],where then give to matched filter,non-correlating detector, by randomised sequence.-take a input vector which is no of users of b[kx1] and
3
- 1、随机生成一个5*5矩阵A,元素符合均匀分布;再随机生成一个5*5矩阵B,元素符合正态分布。对A和B进行加、减、乘、除、比较等矩阵运算,查看运算结果。 2、创建5阶魔术矩阵,求A的行列式、特征值、逆、秩、迹、条件数。 3、假设矩阵 ,求A的LU分解、正交分解、特征值分解、奇异值分解。 4、创建6阶单位稀疏矩阵,并显示其全部元素。 -1, randomly generated a 5* 5 matrix A, elements in line with uniform
work
- matlab 关于association rule 的自己写的函数,有3个文件, association.m:h = association(m, i, j) i=>j, m是数据,h是support和confidence,该函数只适用于单个数据 ass_item: h=ass_itset(m, a, b) 同上,但是可用于多个数据(m为数组) assrule: h = assrule(m, threshold1, threshold2) 该函数用于c
maseidelghhhhhhh
- 用途:用Gauss-Seidel迭代法解线性方程组Ax=b 格式:x=maseidel(A,b,x0,ep,N) A为系数矩阵,b为右端向量, -Uses: The Gauss-Seidel iteration method for solving linear equations Ax = b Format: x = maseidel (A, b, x0, ep, N) A as the coefficient matrix, b for the right-hand side vec
2-76
- 求解大型疏松方程组,ap方程组的系数矩阵,b[放回解向量-For solving large loose equations, ap equations coefficient matrix, b [back into the solution vectors
ols
- 正交最小二乘辨识算法 该算法除了实现最小二乘辨识功能之外而且能按照各项重要性将其逐一选出并且估计相应系数-OLS Orthogonal Least Quares. [x, ind] = OLS(A,b,r) gives the solution to the least squares problem using only the best r regressors chosen from the ones present in matrix A. This
directed_network
- 以邻接矩阵的方式确定有向网,完成: A.建立并显示出它的邻接链表; B.以非递归方式进行深度优先遍历,显示遍历的结果,(并随时显示栈的入出情况); C.对该图进行拓补排序,显示拓补排序的结果,并随时显示入度域的变化情况; D.给出某一确定顶点到所有其他顶点的最短路径-Adjacency matrix to determine a directed network, the completion of: A. To establish and demonstrate its adj
dctcode
- B = irdct2(A) returns the two-dimensional inverse discrete cosine transform of A. The matrix B is the same size as A and contains the discrete cosine transform coefficients B(k1,k2).