IEEE International Conference on Neural Networks - Conference Proceedings
巻
1
ページ
600 - 605
発行年
1995-11-01
ISSN
1098-7576
出版者
IEEE = Institute of Electrical and Electronics Engineers
抄録
Signal classification performance using multilayer neural network (MLNN) and the conventional signal processing methods are theoretically compared under the limited observation period and computational load. The signals with N samples are classified based on frequency components. The comparison is carried out based on degree of freedom the signal detection regions in an N-dimensional signal space. As a result, the MLNN has higher degree of freedom, and can provide more flexible performance for classifying the signals than the conventional methods. This analysis is further investigated throught computer simulations. Multi-frequency signals and the real application, a dial tone receiver, are taken into account. As a result, the MLNN can provide much higher accuracy than the conventional signal processing methods.
Signal classification based on frequency analysis using multilayer neural network with limited data and computations
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