Title :
Adaptive spectral estimation using the conjugate gradient algorithm
Author :
Chang, Pi Sheng ; Willson, Alan N., Jr.
Author_Institution :
Dept. of Electr. Eng., California Univ., Los Angeles, CA, USA
Abstract :
A method for spectral estimation is presented, using the modified conjugate gradient (CG) algorithm. It implements an adaptive version of Pisarenko´s harmonic retrieval method, where the estimates are updated sample-by-sample. First, a constrained unit norm CG algorithm is formulated, then it is recast into an unconstrained minimization problem. The resulting algorithms can be extended to solve the generalized eigensystem problem, when the noise covariance matrix is known a priori. It is shown that the proposed algorithms convergence rate is comparable to that of a least-squares type algorithm, while being computationally more efficient. Performance simulations are shown, and comparisons with some existing methods are provided
Keywords :
adaptive filters; adaptive signal processing; conjugate gradient methods; convergence of numerical methods; covariance matrices; eigenvalues and eigenfunctions; filtering theory; harmonic analysis; minimisation; noise; signal sampling; spectral analysis; Pisarenko´s harmonic retrieval method; adaptive spectral estimation; adaptive transversal filter; algorithms convergence rate; conjugate gradient algorithm; constrained unit norm CG algorithm; generalized eigensystem problem; least-squares type algorithm; noise covariance matrix; performance simulations; unconstrained minimization problem; Adaptive filters; Character generation; Constraint optimization; Convergence; Cost function; Eigenvalues and eigenfunctions; Equations; Finite impulse response filter; Polynomials; Power harmonic filters;
Conference_Titel :
Acoustics, Speech, and Signal Processing, 1996. ICASSP-96. Conference Proceedings., 1996 IEEE International Conference on
Conference_Location :
Atlanta, GA
Print_ISBN :
0-7803-3192-3
DOI :
10.1109/ICASSP.1996.550180
