Other
Scientific paper
Aug 1981
adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=1981itass..29..830j&link_type=abstract
IEEE Transactions on Acoustics, Speech, and Signal Processing, vol. ASSP-29, Aug. 1981, p. 830-845.
Other
13
Extrapolation, Least Squares Method, Parameter Identification, Signal Processing, Spectrum Analysis, Time Series Analysis, Algorithms, Fourier Transformation, Norms, Power Spectra, Prolate Spheroids, Signal To Noise Ratios
Scientific paper
New algorithms useful for extrapolation and spectral estimation of band-limited sequences in one and two dimensions are presented. It is first shown that many of the existing extrapolation algorithms for noiseless observations are unified under the criterion of minimum norm least-squares extrapolation. By going to a conjugate gradient algorithm, convergence and other numerical properties are improved. It is noted that for noisy observations these algorithms could be extended by considering a mean-square extrapolation criterion which gives rise to a mean-square extrapolation filter and to a recursive extrapolation filter. Extension of these algorithms is made for problems in which the signal is known to be periodic. A new set of functions called the periodic-discrete prolate spheroidal sequences, analogous to DPSS, are introduced, and their properties are investigated.
Jain Arun K.
Ranganath S.
No associations
LandOfFree
Extrapolation algorithms for discrete signals with application in spectral estimation does not yet have a rating. At this time, there are no reviews or comments for this scientific paper.
If you have personal experience with Extrapolation algorithms for discrete signals with application in spectral estimation, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Extrapolation algorithms for discrete signals with application in spectral estimation will most certainly appreciate the feedback.
Profile ID: LFWR-SCP-O-1747051