DocumentCode :
1762759
Title :
Superoscillations With Optimum Energy Concentration
Author :
Lee, Dae Gwan ; Ferreira, P.J.S.G.
Author_Institution :
Department of Mathematical Sciences, KAIST, S. Korea
Volume :
62
Issue :
18
fYear :
2014
fDate :
Sept.15, 2014
Firstpage :
4857
Lastpage :
4867
Abstract :
Oscillations of a bandlimited signal at a rate faster than the bandlimit are called “superoscillations” and have applications e.g. in superresolution and superdirectivity. The synthesis of superoscillating signals is a numerically difficult problem. Minimum energy superoscillatory signals seem attractive for applications because (i) the minimum-energy solution is unique (ii) it has the smallest energy cost (iii) it may yield a signal of the smallest possible amplitude. On the negative side, superoscillating functions of minimum-energy depend heavily on cancellation and give rise to expressions that have very large coefficients. Furthermore, these coefficients have to be found by solving equations that are very ill-conditioned. Surprisingly, we show that by dropping the minimum energy requirement practicality can be gained rather than lost. We give a method of constructing superoscillating signals that leads to coefficients and condition numbers that are smaller by several orders of magnitude than the minimum-energy solution, yet yields energies close to the minimum. In contrast with the minimum-energy method, which builds superoscillations by linearly combining functions with an ill-conditioned Gram matrix, our method combines orthonormal functions, the Gram matrix of which is obviously the identity. Another feature of the method is that it yields the superoscillatory signal that maximises the energy concentration in a given set, which may or may not include the superoscillatory segment.
Keywords :
Context; Energy resolution; Image resolution; Optical diffraction; Optical imaging; Optical signal processing; Signal resolution; Algorithms; Hilbert space; interpolation; matrices; nonuniform sampling; numerical stability; optimisation; sampling methods; signal design; superoscillations;
fLanguage :
English
Journal_Title :
Signal Processing, IEEE Transactions on
Publisher :
ieee
ISSN :
1053-587X
Type :
jour
DOI :
10.1109/TSP.2014.2339794
Filename :
6857440
Link To Document :
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