@inproceedings{oai:kanazawa-u.repo.nii.ac.jp:00007507,
 author = {Hara, Kazuyuki and Nakayama, Kenji},
 book = {IEEE International Conference on Neural Networks - Conference Proceedings},
 month = {Nov},
 note = {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.},
 pages = {600--605},
 publisher = {IEEE(Institute of Electrical and Electronics Engineers)},
 title = {Signal classification based on frequency analysis using multilayer neural network with limited data and computations},
 volume = {1},
 year = {1995}
}