Assessment of the Formant Frequencies in Normal and Laryngectomized Individuals Using Linear Predictive Coding

The objective of this study was to assess the difference in voice quality as defined by acoustical analysis using sustained vowel in laryngectomized patients in comparison with normal volunteers. This was designed as a retrospective single center cohort study. An adult tertiary referral unit formed the setting of this study. Fifty patients (40 males) who underwent total laryngectomy and 31 normal volunteers (18 male) participated. Group comparisons with the first three formant frequencies (F1, F2, and F3) using linear predictive coding (LPC) (Laryngograph Ltd, London, UK) was performed. The existence of any significant difference of F1, F2, and F3 between the two groups using the sustained vowel /i/ and the effects of other factors namely, tumor stage (T), chemoradiotherapy, pharyngectomy, cricothyroid myotomy, closure of pharyngoesophageal segment, and postoperative complication were analyzed. Formant frequencies F1, F2, and F3 were significantly different in male laryngectomees compared to controls: F1 (P<0.001, Mann-Whitney U test), F2 (P<0.001, Student's t test), and F3 (P=0.008, Student's t test). There was no significant difference between females in both groups for all three formant frequencies. Chemoradiotherapy and postoperative complications (pharyngocutaneous fistula) caused a significantly lower formant F1 in men, but showed little effect in F2 and F3. Laryngectomized males produced significantly higher formant frequencies, F1, F2, and F3, compared to normal volunteers, and this is consistent with literature. Chemoradiotherapy and postoperative complications significantly influenced the formant scores in the laryngectomee population. This study shows that robust and reliable data could be obtained using electroglottography and LPC in normal volunteers and laryngectomees using a sustained vowel.     

彩虹全息图的假彩色编码方法

本文在三基色原理的基础上，分析了在彩虹全息术中的两种假彩色编码方法——多狭缝假彩色编码方法和参考光假彩色编码方法。     

Wavelet and harmonic filtering for distortion-invariant volume holographic correlation

The wavelet and harmonic filtering method suggested by Zalevsky and Ouzieli is introduced in this paper and adopted in our volume holographic image recognition system. This composite filter combines several scaled versions of the cascaded wavelet and harmonic filter, obtaining high discrimination ability and wide dynamic range of rotation and scale deformations. Optical experiments are conducted to demonstrate the validity and practicability of the algorithm. To the best of our knowledge, this is the first report of using this algorithm in a volume holographic system. Moreover, the separate correlation approach proposed in this paper greatly simplifies the manufacturing process and reduces the cost of the system.     

Decay of the remanent magnetization in the asymmetric spin chain

The dynamics of the one-dimensional spin glass with asymmetric interactions between neighboring spins is considered. We confine ourselves to discrete couplings with values ±J. We show that the algebraic decay of the remanent magnetization of the infinite ±J-spin chain at zero temperature is only valid for symmetric couplings. Our analytical investigations as well as computer simulations show stretched exponential decay for any finite concentration of antisymmetric bonds. Thus, the asymmetric ±J-spin chain shows an asymmetry-induced phase transition at zero temperature.     

A pair of orthogonal frames

We start with a characterization of a pair of frames to be orthogonal in a shift-invariant space and then give a simple construction of a pair of orthogonal shift-invariant frames. This is applied to obtain a construction of a pair of Gabor orthogonal frames as an example. This is also developed further to obtain constructions of a pair of orthogonal wavelet frames.     

SOME TOPICS ON WAVELET ANALYSIS

A review of the advance in the theory of wavelet analysis in recent years is given.     

Multivariate calibration of near infrared spectra by orthogonal WAVElet correction using a genetic algorithm

Orthogonal WAVElet correction (OWAVEC) is a pre-processing method aimed at simultaneously accomplishing two essential needs in multivariate calibration, signal correction and data compression, by combining the application of an orthogonal signal correction algorithm to remove information unrelated to a certain response with the great potential that wavelet analysis has shown for signal processing. In the previous version of the OWAVEC method, once the wavelet coefficients matrix had been computed from NIR spectra and deflated from irrelevant information in the orthogonalization step, effective data compression was achieved by selecting those largest correlation/variance wavelet coefficients serving as the basis for the development of a reliable regression model. This paper presents an evolution of the OWAVEC method, maintaining the first two stages in its application procedure (wavelet signal decomposition and direct orthogonalization) intact but incorporating genetic algorithms as a wavelet coefficients selection method to perform data compression and to improve the quality of the regression models developed later. Several specific applications dealing with diverse NIR regression problems are analyzed to evaluate the actual performance of the new OWAVEC method. Results provided by OWAVEC are also compared with those obtained with original data and with other orthogonal signal correction methods.     

小波包去噪信号的分形特征

将分形理论与小波包滤波相结合，用盒维数的大小来评判信号曲线的滤波情况。随着小波包分解尺度的增大，滤波后信号曲线的盒维数逐渐减小，并最后趋于稳定值。因此可以根据盒维数-分解尺度曲线来选择最佳分解尺度。对仿真含噪信号进行了滤波实验，结果表明：即使在信噪比低至0．5时仍能得到较好的结果，并且该法用于毛细管电泳实验数据的处理结果同样令人满意。     

Simultaneous kinetic determination of thiocyanate and sulfide using eigenvalue ranking and correlation ranking in principal component-wavelet neural network

In this work, two toxic compound, sulfide and thiocyanate were determined simultaneously using kinetic spectrophotometry. These anions have shown the catalytic effects on the reaction between iodine and azide. Since the system was nonlinear, a nonlinear model, principal component-wavelet neural network (PC-WNN) was used as the multivariate calibration method. The principal component analysis was used to decrease the dimension of the original matrix. In other words, the scores of the PCs, 5, instead of the original variables, 301, were used as the input for the model. Two methods were used to select the most relevant principal components: eigenvalue ranking and correlation ranking. In this work, eigenvalue and correlation ranking methods have shown better results for thiocyanate and sulfide, respectively, and it can be concluded that these methods are complementary. The WNN has several advantages relative to other types of neural network such as better convergence ability. The data set was divided to calibration, prediction and validation sets. Each set was selected so that the concentrations of the analytes were approximately covered the entire ranges of the analytes. Mean relative error for thiocyanate and sulfide in validation set were 8.5 and 10.6, respectively. Thiocyanate and sulfide can be determined in the range of 60–700 ng ml⁻¹ and 20–400 ng ml⁻¹, respectively. The proposed method was applied for the determination of sulfide and thiocyanate in real samples such as tap, waste and river waters with satisfactory results.     

小波变换用于高效液相色谱的基线校正

本文根据小波变换将信号分频的性质，用Ｄａｕｂｅｃｈｉｅｓ小波成功地解决了高效液相色谱中基线校正问题，用于定量分析乳酸－稀土络合物体系中的十六个稀土元素，所得结果与仪器给出了结果进行比较，准确度提高，重现性良好。