A new customization approach based on support vector regression （SVR） is proposed to obtain individual headrelated impulse response （HRIR） without complex measurement and special equipment. Principal component ana...A new customization approach based on support vector regression （SVR） is proposed to obtain individual headrelated impulse response （HRIR） without complex measurement and special equipment. Principal component analysis （PCA） is first applied to obtain a few principal components and corresponding weight vectors correlated with individual anthropometric parameters. Then the weight vectors act as output of the nonlinear regression model. Some measured anthropometric parameters are selected as input of the model according to the correlation coefficients between the parameters and the weight vectors. After the regression model is learned from the training data, the individual HRIR can be predicted based on the measured anthropometric parameters. Compared with a back-propagation neural network （BPNN） for nonlinear regression, better generalization and prediction performance for small training samples can be obtained using the proposed PCA-SVR algorithm.展开更多
Borderline personality disorder （BPD） is a serious personality disorder characterized by a pervasive pattern of disturbances in mood regulation, impulse control, self-image and interpersonal relationships） In the U...Borderline personality disorder （BPD） is a serious personality disorder characterized by a pervasive pattern of disturbances in mood regulation, impulse control, self-image and interpersonal relationships） In the United States, the prevalence of BPD has been estimated at 1%-2% of the general population, 10% of psychiatric outpatients, and 20% of inpatients. According to the 4th text revision of diagnostic and statistical manual of mental disorders （DSM-IV-TR）, about 75% of BPD patients are women. The BPD diagnosis has been associated with heightened risk （8.5% to 10.0% among BPD patients） for completed suicide, a rate almost 50 times higher than in the general population.展开更多
基金Project supported by the Shanghai Natural Science Foundation (Grant No.08ZR1408300)the Shanghai Leading Academic Discipline Project (Grant No.S30108)
文摘A new customization approach based on support vector regression （SVR） is proposed to obtain individual headrelated impulse response （HRIR） without complex measurement and special equipment. Principal component analysis （PCA） is first applied to obtain a few principal components and corresponding weight vectors correlated with individual anthropometric parameters. Then the weight vectors act as output of the nonlinear regression model. Some measured anthropometric parameters are selected as input of the model according to the correlation coefficients between the parameters and the weight vectors. After the regression model is learned from the training data, the individual HRIR can be predicted based on the measured anthropometric parameters. Compared with a back-propagation neural network （BPNN） for nonlinear regression, better generalization and prediction performance for small training samples can be obtained using the proposed PCA-SVR algorithm.
基金This research was supported by the Direct Research Grant of The Chinese University of Hong Kong
文摘Borderline personality disorder （BPD） is a serious personality disorder characterized by a pervasive pattern of disturbances in mood regulation, impulse control, self-image and interpersonal relationships） In the United States, the prevalence of BPD has been estimated at 1%-2% of the general population, 10% of psychiatric outpatients, and 20% of inpatients. According to the 4th text revision of diagnostic and statistical manual of mental disorders （DSM-IV-TR）, about 75% of BPD patients are women. The BPD diagnosis has been associated with heightened risk （8.5% to 10.0% among BPD patients） for completed suicide, a rate almost 50 times higher than in the general population.
