Journal
IEEE TRANSACTIONS ON SIGNAL PROCESSING
Volume 68, Issue -, Pages 478-492Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TSP.2019.2961234
Keywords
Variable projection; Model selection; Separable nonlinear least squares; Nonlinear regression; Rational functions; Particle swarm optimization; ECG compression
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Funding
- Hungarian Scientific Research Funds (OTKA) [K115804, EFOP-3.6.3-VEKOP-162017-00001]
- Hungarian Government - European Social Fund [UNKP-17-4]
- New National Excellence Program of the Ministry of Human Capacities
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In this paper we develop an adaptive transform-domain technique based on rational function systems. It is of general importance in several areas of signal theory, including filter design, transfer function approximation, system identification, control theory etc. The construction of the proposed method is discussed in the framework of a general mathematical model called variable projection. First we generalize this method by adding dimension type free parameters. Then we deal with the optimization problem of the free parameters. To this order, based on the well-known particle swarm optimization (PSO) algorithm, we develop the multi-dimensional hyperbolic PSO algorithm. It is designed especially for the rational transforms in question. As a result, the system along with its dimension is dynamically optimized during the process. The main motivation was to increase the adaptivity while keeping the computational complexity manageable. We note that the proposed method is of general nature. As a case study the problem of electrocardiogram (ECG) signal compression is discussed. By means of comparison tests performed on the PhysioNet MIT-BIH Arrhythmia database we demonstrate that our method outperforms other transformation techniques.
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