Applied Mechanics and Materials Vols. 427-429

Abstract: Baseline drift is the main noise of ECG signals which affects the detection accuracy so its removal plays a significantrole in the ECG signal preprocessing. Complex calculation and non-optimal signal processing cause problems of ineffective results and low real-time effects in traditional methods. This paper designs a new filter to remove baseline drift based on the theory of mathematical morphology, which is created by the geometric parameters of the ECG signal. Experiments show that the method can effectively remove the noise of baseline drift by simple computation and is helpful to improve the detection accuracy.

Abstract: For human head pose analysis based on videos, pose is usually estimated on the head patch provided by a tracking module. However, head tracking is very sensitive to the large changes of pose. Therefore, this work locates the head patch in the videos by head detection. Firstly, we use the Adaboost algorithm to detect the human head in the video. Secondly, we present a dimensionality reduction method to process the head patch. Finally, we use the nearest neighbor method to estimate the head pose. The experiment results show: accurate head detecting helps to estimate the head pose. This method can be used for complex conditions of accurate head pose estimation.

Abstract: Starting from the actual demand for eliminating narrowband interference signals common in GNSS receiver, this brief has described basic principles of adaptive filter first based on LMS algorithm, and then analyzed the performance of anti-narrowband interference receiver with bilateral interpolation filter based on above principles. Finally, simulation results shows that compared with that without interference suppression processing, when JSR is 35dB, the Eb/N0 can improve by 5dB by this method; and when compared with theoretical values without interference, the Eb/N0 deteriorates by 1dB. With the increase of interference strength, the interference suppression effect by this method is more significant.

Abstract: The rapidity and tracking accuracy of the stabilized tracking system are mainly influenced by nonlinearity Currently, various methods has concentrated on nonlinear compensation such as optimal control and sliding mode variable structure. However, the optimal control method needs precise mathematical model, and sliding mode variable structure method leads to fluctuations of the output. Thus, this paper firstly builds a physical model of the tracking system, and then designs a differential ahead and disturbance observer (DOB) controller for stabilization loop, and a disturbance observer is used to compensate nonlinearity. A case study of a single-axis motion simulator is presented to validate the proposed method. The experiment result shows that the proposed method can obviously improve the stabilized tracking platforms performance in terms of accuracy and fast tracking ability.

Abstract: This paper introduces the principles and characteristics of Particle Swarm Optimization algorithm, and aims at the shortcoming of PSO algorithm, which is easily plunging into the local minimum, then we proposes a new improved adaptive hybrid particle swarm optimization algorithm. It adopts dynamically changing inertia weight and variable learning factors, which is based on the mechanism of natural selection. The numerical results of classical functions illustrate that this hybrid algorithm improves global searching ability and the success rate.

Abstract: Aiming at the problems of BP network algorithm easily falling into local minimum point, slow converging and the problem that generalization ability can not be guaranteed, a method to improve the PSO is proposed. This method of improved PSO can strengthen the parameters of BP network. Based on this, a license plate recognition algorithm is designed. Some conclusions can be drawn from the experiments: (1) the improved PSO-BP network is stable and robust which can avoid falling into flat areas and local minimum point. (2) the performance and efficiency of license plate recognition based on the improved PSO-BP network is pretty good.

Abstract: To reduce the amount of computing resources, a fast algorithm of the average power spectrum and signal-to-noise ratio was presented based on rigorous derivation of the formula. Also, it proved the rule gained from computational experiments. Besides, a method called fitting-optimization to determine the classification threshold value was proposed. It improves the accuracy by about 7% for human gene.

Abstract: This paper proposes a novel scheme combining Discrete Wavelet Transform (DWT) and Singular Value Decomposition (SVD) for image watermarking. The watermarking image is separated by two parts randomly, then they are embedded into the sub-bands obtained from the original image in DWT domain by modifying the singular value. SVD is applied twice in this scheme.The use of the threshold of Just Noticeable Distortion (JND) based on human visual model determines the embedding strength and position of the watermark, the digital adaptive watermarking algorithm in a combinational domain is realized. The experimental results show that the proposed scheme has a good invisibility and performance of robustness for common attacks, simultaneously enhances the embedding capacity and security.

Abstract: This paper extracts the Gabor phase feature information to classify facial expression. First, preprocessing the image for obtaining the normalization image of pure expression, Gabor transform has good space-frequency localized and multi-directional selectivity, so uses Gabor filter with five frequencies and eight directions to filter the pure expression image. By changing the filter's center frequency, get the optimal image after filtering, and then extract the phase features, carry on the dimension reduction. Finally, with nearest neighbor classifier to classify, a better experimental result had shown in JAFFE database.

Abstract: With the rapid development of various three dimensional scanning devices, the 3D point cloud data of many objects in the real world can be easily obtained. Therefore, research on 3D reconstruction technology based on point cloud has important practical significance. In this paper, first the research background of point cloud reconstruction is analyzed; and then the typical methods for reconstruction are presented and discussed; finally the performance of these methods are analyzed and compared qualitatively, and the development trend in this field is prospected.