Applied Mechanics and Materials Vols. 239-240

Abstract: The article presents a numerical simulation method for 2D resistivity finite difference forward calculation of point source. On the basis of traditional mixed boundary conditions and decomposition of linear equations, Xu's selection of the wave number k for Fourier inverse transform is using to obtain more accurate numerical results. The results show that this approach simplifies the problem of the numerical simulation for two-dimensional geoelectrical field and effectively control the simulation accurac

Abstract: This paper used the timing analysis to statistically analyze the output sequences of many FOGs which were using in the north-finding system. We confirm an optimal model basing the statistic characteristics, and finally advance a fixed algorithm to estimate the parameters of the model. The results show that the modeling method has the universality to the output data of FOGs in the north-finding system, and also can be used to get the precise parameters in order to serve the following filter.

Abstract: This paper proposed a fast boundary reconstruction algorithm based on adaptive gradient vector flow (GVF) deformable model. The novel dynamic GVF field performs faster and wider capture range over original GVF model, which efficiently attracts the model approaching the object contour more quickly and more stably. Based on the approximation error analysis the algorithm can automatically add new knots in contour curve, which makes the accelerated model achieve adaptive adjustment according to local characteristics of the boundary. The improved algorithm can greatly increase the reconstruction accuracy without compromising approximation efficiency. Additional experiments demonstrate the efficient procedure and fine performance of the approach.

Abstract: In this letter, we present a carrier frequency offset estimation method for burst digital transmission, by introducing a step factor into an earlier estimation algorithm to reduce the computational complexity, with little loss of the estimation accuracy. Performance simulations show that this method can separate the estimation range and accuracy, avoiding the weakness of reaching large estimation range at the expense of estimation accuracy.

Abstract: The purpose of the study is to extract the characteristic parameters of the forming crack acoustic emission (AE) signals generated by the metal deep drawing. Time-series analysis and MATLAB were used to adopt independent component analysis (ICA) to isolate the crack AE signals and extracted the characteristic parameters of AE signals. This study isolate the crack AE signals of the drawing parts by the FastICA method based on the maximum negative entropy, the data was processed by MATLAB and the regression model of the various decomposition established by time-series analysis to extract the characteristic parameters of the crack AE signals. The results suggested that this method can isolate the crack AE signals of the deep drawing successfully and can extract the characteristic parameters and distribution maps of the crack AE signals of the metal drawing parts effectively, provide a favorable basis for the judgment of the molding part quality.

Abstract: This paper introduces a new algorithm based on non-linear function to adaptively control step-size which is used for updating separation matrix to extract a target speech source accurately in blind source separation (BSS). The use of fixed step-size parameter of the conventional BSS algorithm usually results in a trade-off between convergence speed and steady-state misadjustment. The presented algorithm will eliminate much of this trade-off. It intelligently regulates the step-size according to the time-varying dynamics of other parameters at each iteration. The desirable ability of the new algorithm to improve convergence speed and steady-state misadjustment is demonstrated by MATLAB simulation results.

Abstract: The concept of Statistical Directional Characteristics (SDCs) is introduced in this paper. The applications of SDCs in Synthetic Aperture Radar (SAR) imagery interpretation are discussed. Two applications, i.e., target recognition and line detection, are raised to demonstrate the effectiveness of the SDCs-based methods. Both numerical and graphical results are presented. According to the experiment results, the SDCs-based methodology shows advantages both in robustness and in efficiency.

Abstract: In this paper, we propose a speech enhancement technique in terms of subspace methods to reduce the white or colored noise in strong background noise environment. This subspace approach based on Karhunen-Loève transform (KLT) and implemented via Principal Component Analysis (PCA). The subspace selection provided by the minimum description length (MDL) criterion. An offset factor generated from the white noise was used to modify the variance to adapt to the specified colored noise. The objective speech quality measures SegSNR have been introduced to evaluate the performance of the proposed method in time domain. A large amount of data and figures testify that our algorithm provides high performance for a large scale of input signal-to-noise ratio (-5~10dB). The performance of our algorithm is assessed in white and colored noise.

Abstract: Independent Component Analysis (ICA) is a powerful method which aims at representing a given random signal as a sum of independent sources. The engineering community, however, works at the distribution function or characteristic function level while makes assertions at the random variable level. This legitimacy of this jump has never been established and consists of a longstanding gap in the ICA literature. In this paper, it is proved that existence of a factorization of characteristic function does imply existence of a corresponding decomposition of random variable into independent sum and thus the gap is bridged. The proof relies on two nontrivial results from probability theory.

Abstract: Objective to introduce a method that use complex valued wavelet transform algorithm for QRS wave group detection in Electrocardiogram signal. It presents a method of marking the crest value and detecting QRS wave group by combining Fbsp wavelet with mexh wavelet. The method is proved to be precise and rapid by applied to detect 10 pieces of the QRS complexes of the ECG 30min-records provided by MIT-BIH Arrhythmia Database.