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The wavelet analysis and neural network for fault diagnosis system in practice has become a hot research topic in the fields of pattern recognition system in recent years. Acoustic emission technology is used for vibrating screen's fault diagnosis in this paper. The energy feature vectors of signals extracted by use of wavelet packet analysis is regarded as neural network input vectors, and the system...
The following topics are dealt with: security of data; power line communication; radio networks; video streaming; telecommunication switching; optical communication; antenna; computer networks; modulation; diversity reception; mobile communication; optimization; artificial intelligence; neural nets; operations research; signal processing; medical computing; microprocessor chips; FPGA; power systems;...
Aiming at some problems such as ldquoover-fitrdquo with ANN modeling, a new type of combined neural network and corresponding optimal modeling method are proposed in this paper. By this method, expectation error (namely, possible minimum error) is firstly estimated according to data quality; then, optimize network structure and choose optimal training result according to the difference between actual...
The following topics are dealt with: intelligent computing and applications; neural network theory and applications; control theory and applications; modeling and simulation; rough set and data mining; intelligent systems; fuzzy systems and applications; factory automation; optimization theory and applications; circuit design and systems; image and signal processing; information security; modeling...
The following topics are dealt with: image processing; computer vision; audio and video signal processing; wireless network; optimization; evolutionary based algorithm; microelectronics; ASIC; system-on-chip; database system; data warehousing; data mining; artificial neural network; fuzzy system; human computer interaction; computer network security; protocol; field programmable gate array; information...
Minimum L1-norm optimization model has found extensive applications in linear parameter estimations. L1-norm model is robust in non Gaussian alpha stable distribution error or noise environments, especially for signals that contain sharp transitions or dynamic processes. However, its implementation is more difficult due to discontinuous derivatives, especially compared with the least-squares model...
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