Tridiagonal matrix with fringes

In summary, there are efficient algorithms available to solve sparse, banded matrices such as the one described in this conversation. These include routines like SPARSE 1.3 and SPARSE-BLAS which are designed specifically for this type of matrix, as well as proprietary options like SPARSPAK. These routines optimize storage and apply pre-conditioning to improve accuracy.
  • #1
maka89
68
4
Hello everyone!

I am trying to solve a large system of linear equations. The form of the matrix is A = T + F. T is basically a tridiagonal matrix and F has two "lines" of numbers running parallel to the diagonal but at some distance. Basically like this one, but not symmetric, nor is it diagonally dominant.

Questions:
Is there any efficient algorithm to solve this kind of matrix?

Is there any way to turn the matrix into a diagonally dominant one, so that a straight forward iterative method could be used?

Could one make a custom iterative method, that does not require diagonal dominance? Would [itex]\overline{x}_{i+1} = T^{-1}(\overline{b}-F \overline{x}_{i}) [/itex] work?
 
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  • #2
There are routines designed to solve sparse, banded matrices.

http://en.wikipedia.org/wiki/Sparse_matrix

http://en.wikipedia.org/wiki/Preconditioner

I would suggest you look at the routines SPARSE 1.3 and SPARSE-BLAS on netlib as these are collections of routines designed to deal with sparse matrices:

http://www.netlib.org/liblist.html

There is also a proprietary set of routines called SPARSPAK which is available from the U of Waterloo in Canada.

In general, these routines will optimize storing the sparse matrix (since most of the elements are zero, a considerable savings in memory space can be obtained) and also apply pre-conditioning to improve the accuracy of the solution.
 

1. What is a tridiagonal matrix with fringes?

A tridiagonal matrix with fringes is a special type of matrix where the only non-zero elements are found on the main diagonal and the diagonals directly above and below the main diagonal. The "fringes" refer to the non-zero elements on the outermost diagonals, which give the matrix a triangular shape.

2. What is the importance of tridiagonal matrices with fringes?

Tridiagonal matrices with fringes have a variety of uses in mathematics and science, including solving systems of linear equations, optimizing mathematical functions, and modeling physical systems.

3. How is a tridiagonal matrix with fringes different from a regular tridiagonal matrix?

A regular tridiagonal matrix only has non-zero elements on the main diagonal and the diagonals directly above and below the main diagonal, while a tridiagonal matrix with fringes also has non-zero elements on the outermost diagonals.

4. What is the most efficient way to store a tridiagonal matrix with fringes?

To save memory and improve computational efficiency, a tridiagonal matrix with fringes can be stored as a compact vector where the non-zero elements on the main diagonal and outermost diagonals are stored in separate arrays.

5. How are tridiagonal matrices with fringes used in real-world applications?

Tridiagonal matrices with fringes are commonly used in fields such as physics, engineering, finance, and computer science. They can be used to solve problems involving linear systems, optimization, and data analysis. Examples include modeling heat flow, analyzing financial risk, and image processing.

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