Title :
A survey of conjugate gradient algorithms for solution of extreme eigen-problems of a symmetric matrix
Author :
Yang, X. ; Sarkar, T.K. ; Arvas, E.
Author_Institution :
Dept. of Electr. & Comput. Eng., Syracuse Univ., NY, USA
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.<>
Keywords :
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; Adaptive signal processing; Algorithm design and analysis; Character generation; Computational complexity; Covariance matrix; Eigenvalues and eigenfunctions; Iterative algorithms; Iterative methods; Signal processing algorithms; Symmetric matrices;
Journal_Title :
Acoustics, Speech and Signal Processing, IEEE Transactions on
