空间自适应正则化超分辨率图像重建

超分辨率图像重建是一个病态问题,在重建过程中需要正则化处理,而正则化重建会引入正则化误差及重建过程中由于病态性而引入的噪声放大误差,且这两类误差均和图像的空间局部特性有关.提出根据图像的局部空间统计特性自适应控制超分辨率图像正则化重建算法,采用图像局部统计方差来区分图像棱边区域及平滑区域,在图像的棱边区域加强图像的约束重建,而在图像的平滑区域加强正则化.实验表明该算法能有效地减小重建误差,算法的信噪比得益优于传统的正则化重建算法及总变分模型重建算法,并且对正则化参数的选择具有一定的鲁棒性.     

基于最小二乘法的HDR图像快速滤噪算法

提出一种针对高动态范围（HDR）图像滤噪的新方法,通过对用于合成HDR的一组图像进行滤噪来实现。在亮度空间中,通过求解加权最小二乘问题拟合L-t直线,并用该直线修正亮度值,从而到达滤噪目的。实验表明该算法运算量小,能有效去除椒盐型噪声,对高斯型噪声抑制效果明显,优于A.&E.(Ahmet&Erit)的加权求和滤噪算法。     

典型炼油装置数据校正技术的研究

化工过程测虽数据作为反映装置运行状况的特征信息,是实现计算机过程控制、模拟、优化和生产管理的基本依据.研究过程数据校正技术,对实现装置优化控制与管理具有重要理论意义和现实意义.现有理论研究大都采用传统统计检验和线性化处理方法,在实际应用有较大局限性.本文在对已有数据校正技术分析的基础上,提出将修正的时间序列分析法用于测量数据校正.综合考虑数据的窄间冗余和时间冗余,充分利用过程的历史数据,建立了时间序列概率模型,并针对含随机误差数据和含过失误差数据两种情况,从时序法平均值、阶跃过程模型等方面详细探讨数据校正方法.将新的数据校正方法用于典型常减压蒸馏装置,结果表明,新方法能够侦破出数据中含有的过失误差;校正值与真值的平均偏差非常小,具有足够的精度保证数据的准确性;修正的时间序列分析法用于数据校正能克服传统方法的局限性.     

Optimal hole shape for minimum stress concentration using parameterized geometry models

The goal of this work is to obtain optimal hole shape for minimum stress concentration in two-dimensional finite plates using parameterized geometry models. The boundary shape for a hole is described by two families of smooth curves: one is a “generalized circular” function with powers as two parameters; the other one is a “generalized elliptic” function a and b are ellipse axes) with powers as two parameters and one of the ellipse axes as the third parameter. Special attention is devoted to the practicability of parameterized equations and the corresponding optimal results under the condition with and without the curvature radius constraint. A number of cases were examined to test the effectiveness of the parameterized equations. The numerical examples show that extremely good results can be obtained under the conditions with and without curvature radius constraint, as compared to the known solutions in the literature. The geometries of the optimized holes are presented in a form of compact parametric functions, which are suitable for use and test by designers. It is anticipated that the implementation of the suggested parameterized equations would lead to considerable improvements in optimizing hole shape with high quality.     

大气湍流图像像素偏差机理分析

对大气湍流导致图像畸变和像素偏差的因素进行了深入分析,对大气湍流状态下激光发射远距离光束的光束漂移均方值进行仿真,分析光束漂移均方值曲线,为后续对图像畸变、像素偏差校正及克服湍流影响提供有效的理论依据。     

Error compensation in machine tools: a neural network approach

For a non-idealized machine tool, each point in the workspace is associated with a tool point positioning error vector. If this error map can be determined, then it is possible to substantially improve the positioning performance of the machine by introducing suitable compensation into the control loop. This paper explores the possibility of using an artifical neural network (ANN) to compute this mapping. The training set for the ANN is obtained by mounting a physical artifact whose dimensions are precisely known in the machine's workspace. The machine, equipped with a touch trigger probe, measures the positions of features on the artifact. The difference between the machine reading and the known dimension is the machine error at that point in the workspace. Using standard modeling techniques, the kinematic error model for a CNC turning center was developed. This model was parameterized by measurement of the parametric error functions using a laser interferometer, electronic levels and a precision square. The kinematic model was then used to simulate the artifact-measuring process and develop the ANN training set. The effect of changing artifact geometry was explored and a machining operation was simulated using the ANN output to provide compensation. The results show that the ANN is capable of learning the error map of a real machine, and that ANN-based compensation can significantly reduce part-dimensional errors.     

A quantized set-membership estimation-based heading control method of unmanned surface vessels under unknown-but-bounded wave-induced disturbances

This paper is concerned with the heading tracking control problem for a network-based unmanned surface vessel (USV) under wave-induced disturbances. Considering the characteristics of the wave-induced disturbances, the unknown-but-bounded (UBB) noise model is adopted. Meanwhile, signal quantization is taken into account due to the limited capacity of the communication channel. Based on these considerations, a novel set-membership based control scheme is proposed, which consists of a set-membership filter (SMF) and a set-membership controller (SMC). In the proposed control scheme, the SMF is designed for providing an ellipsoidal estimation set for the USV at each sampling step, and then the SMC uses the estimation set for producing control input for the USV in order to track the reference. Sufficient conditions are derived for the considered USV system to be asymptotically stable and satisfy the modified set-membership performance constraint. Simulation results verifies the effectiveness of the proposed control scheme.     

从测角后交最佳点位规律看规范规定之不足

本文分析了文献[1]所总结的测角后交两类公式在取得最佳点位时的规律,指出当前规范对此问题规定之不足.     

An improved method for voice pathology detection by means of a HMM-based feature space transformation

This paper presents new a feature transformation technique applied to improve the screening accuracy for the automatic detection of pathological voices. The statistical transformation is based on Hidden Markov Models, obtaining a transformation and classification stage simultaneously and adjusting the parameters of the model with a criterion that minimizes the classification error. The original feature vectors are built up using classic short-term noise parameters and mel-frequency cepstral coefficients. With respect to conventional approaches found in the literature of automatic detection of pathological voices, the proposed feature space transformation technique demonstrates a significant improvement of the performance with no addition of new features to the original input space. In view of the results, it is expected that this technique could provide good results in other areas such as speaker verification and/or identification.     

An improved new error estimation algorithm for optimal filter lengths for stereophonic acoustic echo cancellation

In this paper, we propose an new error estimate algorithm (NEEA) for stereophonic acoustic echo cancellation (SAEC) that is based on the error estimation algorithm (EEA) in [Nguyen-Ky T, Leis J, Xiang W. An improved error estimate algorithm for stereophonic acoustic echo cancellation system. In: International conference on signal processing and communication systems, ICSPCS’2007, Australia; December 2007]. In the EEA and NEEA, with the minimum error signal fixed, we compute the filter lengths so that the error signal may approximate the minimum error signal. When the echo paths change, the adaptive filter automatically adjusts the filter lengths to the optimum values. We also investigate the difference between the adaptive filter lengths. In contrast with the conclusions in [Khong AWH, Naylor PA. Stereophonic acoustic echo cancellation employing selective-tap adaptive algorithms. IEEE Trans Audio, Speech, Lang Process 2006;14(3):785-96, Gansler T, Benesty J. Stereophonic acoustic echo cancellation and two channel adaptive filtering: an overview. Int J Adapt Control Signal Process 2000;4:565-86, Benesty J, Gansler T. A multichannel acoustic echo canceler double-talk detector based on a normalized cross-correlation matrix. Acoust Echo Noise Control 2002;13(2):95-101, Gansler T, Benesty J. A frequency-domain double-talk detector based on a normalized cross-correlation vector. Signal Process 2001;81:1783-7, Eneroth P, Gay SL, Gansler T, Benesty J. A real-time implementation of a stereophonic acoustic echo canceler. IEEE Trans. Speech Audio Process 2001;9(5):513-23, Gansler T, Benesty J. New insights into the stereophonic acoustic echo cancellation problem and an adaptive nonlinearity solution. IEEE Trans. Speech Audio Process 2002; 10(5):257-67, Benesty J, Gansler T, Morgan DR, Sondhi MM, Gay SL. Advances in network and acoustic echo cancellation. Berlin: Springer-Verlag; 2001], our simulation results have shown that the filter lengths can be different. Our simulation results also confirm that the NEEA is better than EEA and SM-NLMS algorithm in terms of echo return loss enhancement.