To resolve the conflicting requirements of measurement precision and real-time performance speed,an im-proved algorithm for pattern classification and recognition was developed. The angular distribution of diffracted ...To resolve the conflicting requirements of measurement precision and real-time performance speed,an im-proved algorithm for pattern classification and recognition was developed. The angular distribution of diffracted light varies with particle size. These patterns could be classified into groups with an innovative classification based upon ref-erence dust samples. After such classification patterns could be recognized easily and rapidly by minimizing the vari-ance between the reference pattern and dust sample eigenvectors. Simulation showed that the maximum recognition speed improves 20 fold. This enables the use of a single-chip,real-time inversion algorithm. An increased number of reference patterns reduced the errors in total and respiring coal dust measurements. Experiments in coal mine testify that the accuracy of sensor achieves 95%. Results indicate the improved algorithm enhances the precision and real-time ca-pability of the coal dust sensor effectively.展开更多
In this paper ,a new approach of pattern recognition for tone classification of Putonghua Which is important for speech recognition of Putonghua is discribed . In this method , four parameters of the fundamental frequ...In this paper ,a new approach of pattern recognition for tone classification of Putonghua Which is important for speech recognition of Putonghua is discribed . In this method , four parameters of the fundamental frequency trajectory are selected based on a large number of statistical experiments . It is assumed that the four parameters satisfy multidimensional Gaussion distribution and a non-Euclidean distance function for each tone class is derived according to the rule of minimum probability of calssification error . the optimal decision results are obtained in a sense of statistics . It is proved that this method provides very satisfactory results by the experiments for speaker-independent tone classification of Putonghua .展开更多
基金Project 50674093 supported by the National Natural Science Foundation of China
文摘To resolve the conflicting requirements of measurement precision and real-time performance speed,an im-proved algorithm for pattern classification and recognition was developed. The angular distribution of diffracted light varies with particle size. These patterns could be classified into groups with an innovative classification based upon ref-erence dust samples. After such classification patterns could be recognized easily and rapidly by minimizing the vari-ance between the reference pattern and dust sample eigenvectors. Simulation showed that the maximum recognition speed improves 20 fold. This enables the use of a single-chip,real-time inversion algorithm. An increased number of reference patterns reduced the errors in total and respiring coal dust measurements. Experiments in coal mine testify that the accuracy of sensor achieves 95%. Results indicate the improved algorithm enhances the precision and real-time ca-pability of the coal dust sensor effectively.
文摘In this paper ,a new approach of pattern recognition for tone classification of Putonghua Which is important for speech recognition of Putonghua is discribed . In this method , four parameters of the fundamental frequency trajectory are selected based on a large number of statistical experiments . It is assumed that the four parameters satisfy multidimensional Gaussion distribution and a non-Euclidean distance function for each tone class is derived according to the rule of minimum probability of calssification error . the optimal decision results are obtained in a sense of statistics . It is proved that this method provides very satisfactory results by the experiments for speaker-independent tone classification of Putonghua .
