DocumentCode :
1029423
Title :
Two methods to deconvolve: L1-method using simplex algorithm and L2-method using least squares and parameter
Author :
Drachman, Byron
Author_Institution :
Michigan State Univ., East Lansing, MI USA
Volume :
32
Issue :
3
fYear :
1984
fDate :
3/1/1984 12:00:00 AM
Firstpage :
219
Lastpage :
225
Abstract :
If r(t) is the linear scattering response of an object to an excitation waveform e(t) , then r(t) = (e \\ast h) (t) . One would like to deconvolve and solve for h(t) , the impulse response. It is well-known that this is often an ill-conditioned problem. Two methods are discussed. The first method replaces the discretized matrix form E \\cdot H = R by the following problem. Minimize |h_{1}|+ \\ldots + |h_{n}| subject to R - \\lambda \\leq E \\cdot H \\leq R + \\lambda where \\lambda is a column vector chosen sufficiently small to yield acceptable residuals, yet large enough to make the problem well-conditioned. This problem is converted to a linear programming problem so that the simplex algorithm can be used. The second method is to minimize \\parallel E \\cdot H - R \\parallel^{2} +\\lambda \\parallel H \\parallel^{2} where again \\lambda is chosen small enough to yield acceptable residuals and large enough to make the problem well-conditioned. The method will be demonstrated with a Hilbert matrix inversion problem, and also by the deconvolution of the impulse response of a simple target from measured data.
Keywords :
Deconvolution; Electromagnetic (EM) scattering; Numerical methods; System identification, linear systems; Convolution; Deconvolution; Filtering; Frequency domain analysis; Least squares methods; Linear programming; Mathematics; Scattering parameters; Signal processing; Vectors;
fLanguage :
English
Journal_Title :
Antennas and Propagation, IEEE Transactions on
Publisher :
ieee
ISSN :
0018-926X
Type :
jour
DOI :
10.1109/TAP.1984.1143312
Filename :
1143312
Link To Document :
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