How Far Should You Go With the Lanczos Process.
Final memorandum rept.,
CALIFORNIA UNIV BERKELEY ELECTRONICS RESEARCH LAB
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The Lanczos algorithm can be used to approximate both the largest and smallest eigenvalues of a symmetric matrix whose order is so large that similarity transformations are not feasible. The algorithm builds up a tridiagonal matrix row by row and the key question is when to stop. An analysis leads to a stopping criterion which is inspired by a useful error bound on the computed eigenvalues. Author
- Theoretical Mathematics