Inverse filtering


Brief description of the problem:
Our aim is to measure broad band time or other domain waveforms. If
the bandwidth of the signal to be measured is larger than that of the measurement
system the recorded waveform will be a distorted version of the original
one. Assuming that the distortion is known the measurement can be partly
compensated for it. This process is called inverse filtering.
The main problem of the inverse filtering process is that measurement
noise (quantization noise, electromagnetic interference etc.) is amplified
in a great extent, hiding many times the useful signal completely. This
noise has to be suppressed on the price of bias in the reconstructed signal.
A good compromise has to be found between the noisy and biased reconstruction.
The inverse filtering process should be adaptive to the signal to be measured
and to the noise.
Applications:
Research grants:
 "CyberPhysical Systems"
European Union, European Social Fund (TÁMOP4.2.2.C11/1/KONV20120001), 20122014, 3 years. Principal investigator: T. Dabóczi
 "Parameter Estimation and Modelling, Based on Signal Processing"
Hungarian Scientific Research Fund, 20082011, 3 years. Principal investigator: I. Kollar
 "Model Based Digital Signal Processing"
Hungarian Scientific Research Fund, 20052008, 3 years. Principal investigator: I. Kollar
 "Global optimization of inverse filtering and identification"
Hungarian Scientific Research Fund, 20012003, 3 years. Principal investigator: T. Dabóczi.

"Inverse filtering and its applications " (Ref. No: OTKA F026136) Hungarian
Scientific Research Fund, 19982000, 3 years. Principal investigator: T.
Dabóczi.

"Deconvolution of Fast Electrical Pulses for Standard Purposes " (Ref.
No: 43NANB614883) National Institute of Standards and Technology
(NIST), USA, 199697, 1 year. Principal investigator: T. Dabóczi.

"Intelligent deconvolution system" (Ref. No: OTKA F016457) Hungarian Scientific
Research Fund, 19951997, 3 years. Principal investigator: T. Dabóczi.

"Investigation, development and application of deconvolution algorithms"
(Ref. No.:OTKA780) Hungarian Scientific Research Fund, 19911994, 4 years.
Principal investigator: I. Kollár.
Publications
Contact person:
Tamás Dabóczi, PhD
Dept. of Measurement and Information Systems
Budapest University of Technology and Economics
H1521 Budapest, Hungary
Phone: +36 1 4632065
Fax: +36 1 4634112
Url: http://www.mit.bme.hu/~daboczi/
Email: daboczi@mit.bme.hu