ABSTRACT
@#Difficulty of understanding speech in noise among the elderly necessitates the need for Auditory Training which has made a renewal of interest in the last decade with the auditory training applications. This interest is perhaps spurred by advances in computer-based technology. In computer-based auditory training, speech signals are considered as auditory training stimuli where input speech signals need to be verified prior to training as the speech signals are mixed with noise signals. Computer-based Auditory Training System can be embedded with input speech verifying module. Input speech verifying module is employed with speech and noise separator simulator. This simulator needs to guarantee accurate separation of speech from noise signals. Therefore, in this research, Exploratory Projection Pursuit (EPP) technique under semi-Blind Source Separation (BSS) method is intended to separate the speech source signals which are mixed with competing speech (multitalker speech babble). This training uses Malay language based sentences which differ in word length and hence number of sample values. The experimental simulation considers two-channel random, linear mixing of speech sources and competing speech. The aim of this study is to evaluate the performance of source separation using the anticipated EPP technique for various sample values of speech signals which varies in time duration due to word length dissimilarity. Simulation results show that EPP technique is feasible for source separation. As a consequence, high correlation value of r ≥ 0.99 is obtained between extracted speech signal and original speech signal for all categories of speech signals. It is further verified by the maximum nongaussianity of extracted speech signal which has high kurtosis value of 32 approximately.
ABSTRACT
Objective To compare the difference of effect between principal component regression analysis and projection pursuit regression analysis when collinearity exists in data.Methods Evaluating the advantages and disadvantages of the two modeling methods by using the actual data on two aspects:the fitting effect and the predicting effect.Results The principal component regression model showed that the coefficient of determination was 0.8172,the mean of absolute relative error was 6.42％ and the mean square of prediction error was 0.61.The projection pursuit regression model,on the other hand,showed that the coefficient of determination ranged from 0.8851 to 0.9944,the mean of absolute relative error ranged from1.11％ to 4.81％ and the mean square of prediction error ranged from 0.03 to 0.38.Conclusion The analysis results based on the actual data with collinearity indicate that the projection pursuit regression analysis outperforms the principal component regression analysis both in fitting and predicting effect.
ABSTRACT
Objective To evaluate the quality of Isatidis Radix from different ecotypes by using projection pursuit model. Methods Totally 11 batches of Isatidis Radix from different ecotypes in Gansu Province were used as evaluation samples. With the contents of epigoitrin, uridine, guanosine, adenosine, benzoic acid, salicylic acid, indigo, indirubin, and alcohol extract as evaluating indexes, combined with projection pursuit model established by DPS V 9.50 statistics software, the quality of Isatidis Radix was evaluated. Results Based on the evalution of nine main indexes, quality order of the 11 batches of Isatidis Radix was acquired: S2>S1>S9>S7>S8>S3>S5>S10>S11>S4>S6. Conclusion The projection pursuit model was available for the quality evaluation of different ecotype Isatidis Radix. The quality of Isatidis Radix from different ecotypes is different significantly, and the quality of tetraploid Isatidis Radix of Shijiazhuang is the best.
ABSTRACT
Objective To explore the application of projection pursuit model in anti-assessment on peer reviewer of scientific research project,discussing the rational of this application.Methods Establishing the projection pursuit model of anti-assessment on peer reviewer,with the best projection direction as a weight,making an evaluation on the peer reviewer,and sequencing experts by projection value.Results The projection pursuit model is stable and scientific,the importance of index ranking as correlation coefficient＞ dispersion＞ hit rate＞ synthetic dispersion＞ self dispersion ratio.Conclusions The application of projection pursuit model in anti-assessment on peer reviewer of scientific research project,is reasonable and practicable.