TY - JOUR
T1 - Adaptive Algorithms for Constrained ARMA Signals in the Presence of Noise
AU - Nehorai, Arye
AU - Stoica, Petre
N1 - Funding Information:
Manuscript received April 11, 1987; revised February 3, 1988. The work of A. Nehorai wa5 supported by the Air Force Office of Scientific Research under Grant AFOSR-88-0080. A. Nehorai is with the Department of Electrical Engineering, Yale University, New Haven, CT 06520. P. Stoica is with the Department of Automatic Control, Polytechnic In- stitute of Bucharest, Splaiul lndependentei 313, R-77 206 Bucharest, Romania. IEEE Log Number 8821855.
PY - 1988/8
Y1 - 1988/8
N2 - A new family of algorithms is developed for adaptive parameter estimation of constrained autoregressive moving-average (ARMA) signals in the presence of noise. These algorithms utilize a priori known information about the signal’s properties, such as its spectral type (for example, low pass, band pass, etc.) or a spatial domain characteristic. Special applications include modeling of autoregressions (AR) and signals of known spectral type in the presence of noise, signal deconvolution, image deblurring, and multipath parameter estimation. Selected results of simulations are included to demonstrate the performance of the proposed algorithms.
AB - A new family of algorithms is developed for adaptive parameter estimation of constrained autoregressive moving-average (ARMA) signals in the presence of noise. These algorithms utilize a priori known information about the signal’s properties, such as its spectral type (for example, low pass, band pass, etc.) or a spatial domain characteristic. Special applications include modeling of autoregressions (AR) and signals of known spectral type in the presence of noise, signal deconvolution, image deblurring, and multipath parameter estimation. Selected results of simulations are included to demonstrate the performance of the proposed algorithms.
UR - http://www.scopus.com/inward/record.url?scp=0024056525&partnerID=8YFLogxK
U2 - 10.1109/29.1656
DO - 10.1109/29.1656
M3 - Article
AN - SCOPUS:0024056525
SN - 0096-3518
VL - 36
SP - 1282
EP - 1291
JO - IEEE Transactions on Acoustics, Speech, and Signal Processing
JF - IEEE Transactions on Acoustics, Speech, and Signal Processing
IS - 8
ER -