Performance of the SMLR deconvolution algorithm

Author

Chi, Chong-Yung

Author_Institution

Dept. of Electr. Eng., Nat. Tsing Hua Univ., Hsinchu, Taiwan

Volume

39

Issue

9

fYear

1991

fDate

9/1/1991 12:00:00 AM

Firstpage

2082

Lastpage

2086

Abstract

A performance analysis is presented for false alarms, correct detections, and the resolution of the suboptimal maximum-likelihood deconvolution (MLD) algorithm, called the single most likely replacement (SMLR) algorithm. It is assumed that the source wavelet and statistical parameters are given a priori. It is shown analytically that the performance improves as the signal-to-noise ratio (SNR) increases and as the mainlobe width of the normalized autocorrelation function of the source wavelet decreases. For the same performance, a higher SNR is required as the mainlobe width of the normalized autocorrelation function increases. Some simulation results which are consistent with the analytic results are presented

Keywords

estimation theory; noise; signal processing; SMLR deconvolution algorithm; SNR; correct detections; estimation theory; false alarms; mainlobe width; normalized autocorrelation function; performance analysis; signal processing; signal-to-noise ratio; single most likely replacement; source wavelet; statistical parameters; suboptimal maximum-likelihood deconvolution; Analytical models; Autocorrelation; Convolution; Covariance matrix; Deconvolution; Maximum likelihood detection; Performance analysis; Seismic measurements; Signal processing algorithms; Signal to noise ratio;

fLanguage

English

Journal_Title

Signal Processing, IEEE Transactions on

Publisher

ieee

ISSN

1053-587X

Type

jour

DOI

10.1109/78.134440

Filename

134440