Abstract
In this article the stochastic algorithms (particle swarm algorithm, simulated annealing algorithm, and genetic selection algorithm) applied to the problem of an adaptive calculation of the low pass filter parameters are compared. The data used for the filtration were obtained from the sensor (accelerometer) by implementing the software package for recording a human walking motion. For the algorithms comparison, the math library was implemented. The purpose of the study was to obtain optimum characteristics of moving average method by means of the algorithms described in this paper. The results of numerical experiments have shown that the best results have been obtained using the particle swarm algorithm and the genetic selection algorithm.
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© 2014 Springer International Publishing Switzerland
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Rogoza, V., Sergeev, A. (2014). The Comparison of the Stochastic Algorithms for the Filter Parameters Calculation. In: Swiątek, J., Grzech, A., Swiątek, P., Tomczak, J. (eds) Advances in Systems Science. Advances in Intelligent Systems and Computing, vol 240. Springer, Cham. https://doi.org/10.1007/978-3-319-01857-7_23
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DOI: https://doi.org/10.1007/978-3-319-01857-7_23
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-01856-0
Online ISBN: 978-3-319-01857-7
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