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- W2171790926 abstract "Signal classification performance using both multilayer neural network (MLNN) and conventional signal processing methods are theoretically compared under a limited observation period and computational load. Signals with N samples are classified based on the frequency components. A comparison is carried out based on the degree of freedom of the signal detection regions in an N-dimensional signal space. As a result, the MLNN has a higher degree of freedom, and can provide a more flexible performance for classifying the signals than the conventional methods. This analysis is further investigated through computer simulations. Multi-frequency signals and a real application in dial tone receiver, are considered. As a result, the MLNN can provide a much higher accuracy than the conventional signal processing methods." @default.
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- W2171790926 date "2002-11-19" @default.
- W2171790926 modified "2023-09-25" @default.
- W2171790926 title "Signal classification based on frequency analysis using multilayer neural network with limited data and computation" @default.
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- W2171790926 doi "https://doi.org/10.1109/icnn.1995.488247" @default.
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