Name
Title | ||
|---|---|---|
A survey of conjugate gradient algorithms for solution of extreme eigen-problems of a symmetric matrix |
Abstract | ||
|---|---|---|
A survey of various conjugate gradient (CG) algorithms is presented for the minimum/maximum eigen-problems of a fixed symmetric matrix. The CG algorithms are compared to a commonly used conventional method found in IMSL. It is concluded that the CG algorithms are more flexible and efficient than some of the conventional methods used in adaptive spectrum analysis and signal processing.<> |
Year | DOI | Venue |
|---|---|---|
1989 | 10.1109/29.35393 | Acoustics, Speech and Signal Processing, IEEE Transactions |
Keywords | Field | DocType |
eigenvalues and eigenfunctions,matrix algebra,signal processing,spectral analysis,adaptive signal processing,adaptive spectrum analysis,conjugate gradient algorithms,extreme eigen-problems,maximum eigenvalue,minimum eigenvalue,symmetric matrix | Conjugate gradient method,Signal processing,Mathematical optimization,Eigenvalue algorithm,Positive-definite matrix,Algorithm,Symmetric matrix,Hamiltonian matrix,Hermitian matrix,Mathematics,Derivation of the conjugate gradient method | Journal |
Volume | Issue | ISSN |
37 | 10 | 0096-3518 |
Citations | PageRank | References |
53 | 29.71 | 7 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yang, X. | 1 | 53 | 29.71 |
| Sarkar, T.K. | 2 | 471 | 117.33 |
| Ercument Arvas | 3 | 57 | 32.83 |