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Noise immunity analysis of neuron-like algorithms in acoustic image processing

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Abstract

There exists the problem of pre-selection of the most noise-immune algorithms (including the neuron-like ones) when acoustic signals are proceesed in subwater acoustic vision systems. A software version is considered for choosing the parameters in the acoustic image processing algorithms which improve the noise immunity of the decision-making process. It is shown that the processing modes with improved noise immunity can be chosen in model experiments associated with threshold changes in the neuron-like transformation algorithms.

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Authors
  1. S. M. Gorsky
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  2. E. B. Kurzenin
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  3. A. I. Khil'ko
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  4. V. G. Yakhno
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Additional information

Institute of Physics, Russian Academy of Sciences, Nizhny Novgorod. Translated from Izvestiya Vysshikh Uchebnykh Zavedenii, Radiofizika, Vol. 37, No. 9, pp. 1214–1223, September, 1994.

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Gorsky, S.M., Kurzenin, E.B., Khil'ko, A.I. et al. Noise immunity analysis of neuron-like algorithms in acoustic image processing. Radiophys Quantum Electron 37, 784–789 (1994). https://doi.org/10.1007/BF01039619

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  • DOI: https://doi.org/10.1007/BF01039619

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