镜像matrix在matlab里怎么做呢？

镜像matrix在matlab里怎么做呢？

这个要用function做。
1.设num=0; flag=0; 后如果是n阶矩阵的话设为1到n（i=1:n),而num是要等于i的。设b＝2，则在loop用到j=1:n.
2.当i和j是一样的（i=j), data(i,j)=1,flag也是1。
3。当 flag=0，那么data(i,j)=num; num=num-1;
4。当 flag==1，data(i,j)=b;而 b=b+1;

a = flipdim(a,1); % Flips the rows of a a = flipdim(a,2); % Flips the columns of a EDIT: An additional little trick... if for whatever reason you have to flip BOTH dimensions of a 2-D array, you can either call FLIPDIM twice: a = flipdim(flipdim(a,1),2); or call ROT90: a = rot90(a,2); % Rotates matrix by 180 degrees

matlab里的'/'不完全等于矩阵除法。 你可以用help mrdivide看一下'/'的帮助： >> help mrdivide / slash or right matrix divide. a/b is the matrix division of b into a, which is roughly the same as a*inv(b) , except it is computed in a different way. more precisely, a/b = (b'\a')'. see mldivide for details. 就是说a/b可以大致看成a*inv(b)，但用的是另一种方法。更确切的讲a/b = (b'\a')'。 那再看看'\'(左除或者反除)是什么东东。 >> help mldivide \ backslash or left matrix divide. a\b is the matrix division of a into b, which is roughly the same as inv(a)*b , except it is computed in a different way. if a is an n-by-n matrix and b is a column vector with n components, or a matrix with several such columns, then x = a\b is the solution to the equation a*x = b computed by gaussian elimination. a warning message is printed if a is badly scaled or nearly singular. a\eye(size(a)) produces the inverse of a. if a is an m-by-n matrix with m < or > n and b is a column vector with m components, or a matrix with several such columns, then x = a\b is the solution in the least squares sense to the under- or overdetermined system of equations a*x = b. the effective rank, k, of a is determined from the qr decomposition with pivoting. a solution x is computed which has at most k nonzero components per column. if k < n this will usually not be the same solution as pinv(a)*b. a\eye(size(a)) produces a generalized inverse of a. 就是说当a是n阶方阵b为n行的列向量时，x=a\b就是线性方程组a*x=b的解，算法是用高斯消去法。a\eye(size(a))产生的是方阵a的逆矩阵。 如果a是m*n的矩阵且m≠n，b是跟a行数(m行)相同的列向量时，x=a\b是非满秩的线性方程组a*x=b的解系，a的秩k由qr分解得出。如果k> a=pascal(3) %a赋值为3*3的方阵。 a = 1 1 1 1 2 3 1 3 6 >> b=[1:3]' % b是3*1的列向量。 b = 1 2 3 >> x=a\b % 用反除求ax=b的解，结果x是个列向量，注意是a\b不是b\a x = 0 1 0 >> a*x % 验证一下a*x刚好等于b ans = 1 2 3 >> x=b'/a' % 这回是正除了，不过b'是行向量，a'也倒一下，正除的时候就是b'/a'了，不是a'/b'了，结果x是个行向量 x = 0 1 0 >> x*a' % 验证一下，跟b'一样。 ans = 1 2 3 >> a=rand(3,4) % 这回重新赋值，a不是方阵了，是3*4的矩阵 a = 0.5298 0.3798 0.4611 0.0592 0.6405 0.7833 0.5678 0.6029 0.2091 0.6808 0.7942 0.0503 >> x=a\b % 实际上方程组没有唯一确定的解，而是无数解，所以解出来的是一个特解 x = -1.5132 4.9856 0 -1.5528 >> a*x % 验证，跟b相等。 ans = 1.0000 2.0000 3.0000 >> a=rand(3,2) % 再看看3*2的矩阵，行数>列数的情况 a = 0.4154 0.0150 0.3050 0.7680 0.8744 0.9708 >> x=a\b x = 1.8603 1.5902 >> a*x % 验证一下，嗯？怎么不等于b了？ ans = 0.7966 1.7886 3.1704 % 为什么呢？因为方程数(行数)太多，未知数(列数)个数太少，2个未知数，用2个线性无关的方程就可以求确定的解了，现在方程多了，不能同时满足所有方程，所以实际上是无解，只不过matlab里用的是一个最小二乘意义上的近似解，所以验证时不等，只是尽可能近似的满足所有方程。 另外,团idc网上有许多产品团购,便宜有口碑