A fuzzy-neural network needs to be trained through a learning process, so that suitable membership functions and weightings can be obtained. However, most neural networks are only simulated by computer software, which are not practical for real applications. It is therefore our objective to design an integrated circuit system based on a DSP processor with powerful arithmetical capabilities and fast data processing, and relevant peripheral devices to implement the fuzzy-neural network. In terms of implementation cost and feasibility for practical applications, this DSP-based fuzzy-neural network will be more practical and usable. Finally, a prospective application of the DSP-processor-based fuzzy neural network to recognize speech from a non-designated person is proposed.
|Journal||Proceedings of the IEEE International Conference on Systems, Man and Cybernetics|
|Publication status||Published - 1999|
ASJC Scopus subject areas
- Hardware and Architecture
- Control and Systems Engineering