Title :
A practical stopping rule for iterative signal restoration
Author :
Perry, Kevin M. ; Reeves, Stanley J.
Author_Institution :
Dept. of Electr. Eng., Auburn Univ., AL, USA
fDate :
7/1/1994 12:00:00 AM
Abstract :
Iterative signal restoration is a common and simple approach for recovering degraded signals. Unfortunately, iterative algorithms often converge slowly, and the convergence point is usually not the best restoration because of noise amplification. Therefore, a stopping rule should be imposed to maximize the effectiveness of the iterative algorithm. We demonstrate the value of randomized generalized cross-validation (RGCV) as a stopping rule for linear iterative restoration algorithms with simple initial conditions and show that it can be used on relatively small data sets with confidence. We also illustrate the performance of the RGCV criterion for various degrees of blurring and noise
Keywords :
convergence of numerical methods; iterative methods; signal processing; blurring; degraded signal recovery; initial conditions; iterative signal restoration; linear iterative restoration algorithms; noise amplification; randomized generalized cross-validation; stopping rule; Adaptive arrays; Antennas and propagation; Array signal processing; Covariance matrix; Erbium; Frequency; Interference; Signal restoration; Signal to noise ratio; White noise;
Journal_Title :
Signal Processing, IEEE Transactions on