| Summary: | 碩士 === 國立交通大學 === 資訊工程研究所 === 82 === Recently, the studies of artificial neural network have
attracted the attention of more and more researchers from
various fields. It is important to design and implement neural
networks on a systematic and hierarchical methodology. In this
thesis, we develop the hierarchical design flow and follow this
flow to design, analyze, simulate and implement to solve Morse
Codes Recognition System. In the recognition system design, we
were aware that a high performance system which contains both
neural networks and traditional method system. Therefore, we
propose a hybrid neural network system in this thesis. The
design of hierarchical approaches is to analyze problem and
then divided the problem into several parts. The major function
of each part should be clearly defined in advance. Then, we
find some methods to achieve its function and choose the best
one. Finally, integration of each part is required. With
hierarchical design flow, Morse Codes recognition system is
divided into three subsystems, preprocessing, feature
extraction and code recognition. In order to achieve high
performance, we use hybrid neural network to design this
system. There are two advantages in hybrid neural network,
training time reduced and the better results than only one
method is used. In our experiment, the training time in MLP
network is about three times the time in the hybrid neural
network. The final correct rates in the hybrid neural network
and MLP network are 90\% and 82\% respectively. But we should
note that only the suitable input values result in better
performance and training time reducing. Consequently, The
hierarchical design and hybrid neural network lead to the
better results in Morse Codes Recognition System.
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