If we have two individually sorted VectorS "a" and "b" but they are not sorted with respect to each other and we want to merge them into vector "c" such that "c" is also a sorted vector. Then c=mergesorted(a,b) can be used.
The inverse of the gradient function. I ve provided versions that work on 1-d VectorS, or 2-d or 3-d arrays. In the 1-d case I offer 5 different methods, from cumtrapz, and an integrated cubic spline, plus several finite difference methods.
In higher dimensions, only a finite difference/linear algebra solution is provided, but it is fully vectorized and fully sparse in its approach. In 2-d and 3-d, if the gradients are inconsistent, then a least squares solution is generated
Circular Convolution of two equal-length VectorS. Highlights that circular convolution in the time domain is the effectively the same as element-by-element multiplication in the frequency domain.
Initialize U=[uij] matrix, U(0)
At k-step: calculate the centers VectorS C(k)=[cj] with U(k)
Update U(k) , U(k+1)
If || U(k+1) - U(k)||< then STOP otherwise return to step 2.
