DocumentCode
2503324
Title
Kernels for reconstructing nonideally sampled nonbandlimited signals
Author
Guevara, Alvaro ; Mester, Rudolf
Author_Institution
Visual Sensorics & Inf. Process. Lab., Goethe Univ., Frankfurt am Main, Germany
fYear
2011
fDate
28-30 June 2011
Firstpage
105
Lastpage
108
Abstract
Deviating from classical Shannon-type sampling, we determine the MMSE-optimum reconstructions kernels for linearly interpolating a non-bandlimited signal from a discrete set of noisy measurements obtained from non-δ sampling kernels. For this purpose, the first and second order moment functions (ACF) of the continuous input process are required. We provide examples showing how the input autocorrelation, the sampling kernel, and the input noise level shape the form of the optimal interpolating kernels.
Keywords
interpolation; least mean squares methods; signal reconstruction; signal sampling; ACF; MMSE-optimum reconstruction kernel; Shannon-type sampling; nonideal sampled nonbandlimited signal reconstruction; optimal interpolating kernels; second order moment functions; Correlation; Interpolation; Kernel; Signal to noise ratio; Spline; Sampling; interpolation; reconstruction;
fLanguage
English
Publisher
ieee
Conference_Titel
Statistical Signal Processing Workshop (SSP), 2011 IEEE
Conference_Location
Nice
ISSN
pending
Print_ISBN
978-1-4577-0569-4
Type
conf
DOI
10.1109/SSP.2011.5967632
Filename
5967632
Link To Document