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National Repository of Grey Literature 3 records found  Search took 0.01 seconds. 
Bandlimited signals, their properties and extrapolation capabilities
 Mihálik, Ondrej ; Havránek, Zdeněk (referee) ; Jura, Pavel (advisor)
The work is concerned with the band-limited signal extrapolation using truncated series of prolate spheroidal wave function. Our aim is to investigate the extent to which it is possible to extrapolate signal from its samples taken in a finite interval. It is often believed that this extrapolation method depends on computing definite integrals. We show an alternative approach by using the least squares method and we compare it with the methods of numerical integration. We also consider their performance in the presence of noise and the possibility of using these algorithms for real-time data processing. Finally all proposed algorithms are tested using real data from a microphone array, so that their performance can be compared.
Detailed record
Band-Limited Signal Extrapolation Using Least Squares Approximation By Prolate Spheroidalwave Functions
 Mihálik, Ondrej
This paper is concerned with the band-limited signal extrapolation using a truncated series of Prolate spheroidal wave functions. Our aim is to investigate the extent to which it is possible to extrapolate signal from its samples taken in a finite interval. It is often believed that this extrapolation method depends on computing definite integrals. We show an alternative approach by using the least squares method. We briefly discuss performance of these two methods in the presence of noise and the possibility of using this algorithm for real-time data processing. Finally the extrapolation algorithm is tested with real data from a microphone array.
Detailed record
Bandlimited signals, their properties and extrapolation capabilities
 Mihálik, Ondrej ; Havránek, Zdeněk (referee) ; Jura, Pavel (advisor)
The work is concerned with the band-limited signal extrapolation using truncated series of prolate spheroidal wave function. Our aim is to investigate the extent to which it is possible to extrapolate signal from its samples taken in a finite interval. It is often believed that this extrapolation method depends on computing definite integrals. We show an alternative approach by using the least squares method and we compare it with the methods of numerical integration. We also consider their performance in the presence of noise and the possibility of using these algorithms for real-time data processing. Finally all proposed algorithms are tested using real data from a microphone array, so that their performance can be compared.
Detailed record

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