粘合衬对服装舒适性影响的研究

探讨了粘合衬与粘合工艺对服装透气性、透湿性及透水性影响的规律。得出服装的舒适性虽由面料决定,但辅料(粘合衬)的影响也不可忽视。粘合衬的涂胶种类,粘合衬本身的透气性与透湿性,以及非织造粘合衬底布的单位重量,机织粘合衬底布的覆盖系数等,均对服装舒适性有影响,从而为衬料的选择,以及粘合工艺参数的设定,提供了依据。     

两个组合恒等式的概率证明

给出了两个组合恒等式的概率证明，扩展了已知的结果。     

含有纯滞后对象的控制方法

评述纯滞后对象控制的两种典型方法─—大林算法和纯滞后补偿法的原理、优缺点、设计要求及存在问题，并讨论了两者的联系。     

Non-Minimum Phase Nonlinear System Predictive Control Based on Local Recurrent Neural Networks

Abstract: After a recursive multi-step-ahead predictor for nonlinear systems based on local recurrent neural networks isintroduced, an intelligent PID controller is adopted to correct the errors including identified model errors and accumulatederrors produced in the recursive process. Characterized by predictive control, this method can achieve a good controlaccuracy and has good robustness. A simulation study shows that this control algorithm is very effective.     

Dynamic Characteristics of Inter-Satellite Links in LEO Networks

To establish an efficient inter-satellite link (ISL) in an LEO network, the effect of geometric characteristics of ISL on the ISLs and the devices on the LEO satellite should be examined. Because of the continuous movement of the LEO satellite, the time-varying behaviours of the ISL's geometric charactersistics continuously change with the changes of the satellite's position on the orbit. These dynamic geometric characteristics of the ISLs are important for ISL's performance analyzing and the design of the devices on the LEO satellite. This paper describes dynamic geometric characteristics of ISL, analyzes the impact of these regulations on the tracking system of the satellite's antenna and the power adjusting system of the satellite's transmitter, with the Iridium system as an example.     

Radar Imaging Based on Iterative Algorithms

It has long been realized that the problem of radar imaging is a special case of image reconstruction in which the data are incomplete and noisy. In other fields, iterative reconstruction algorithms have been used successfully to improve the image quality. This paper studies the application of iterative algorithms in radar imaging. A discrete model is first derived, and the iterative algorithms are then adapted to radar imaging. Although such algorithms are usually time consuming, this paper shows that, if the algorithms are appropriately simplified, it is possible to realize them even in real time. The efficiency of iterative algorithms is shown through computer simulations.     

Face Recognition Based on Support Vector Machine and Nearest Neighbor Classifier

Support vector machine (SVM), as a novel approach in pattern recognition, has demonstrated a success in face detection and face recognition. In this paper, a face recognition approach based on the SVM classifier with the nearest neighbor classifier (NNC) is proposed. The principal component analysis (PCA) is used to reduce the dimension and extract features. Then one-against-all stratedy is used to train the SVM classifiers. At the testing stage, we propose an al-     

Subset threshold autoregression

We develop in this paper an efficient way to select the best subset threshold autoregressive model. The proposed method uses a stochastic search idea. Differing from most conventional approaches, our method does not require us to fix the delay or the threshold parameters in advance. By adopting the Markov chain Monte Carlo techniques, we can identify the best subset model from a very large of number of possible models, and at the same time estimate the unknown parameters. A simulation experiment shows that the method is very effective. In its application to the US unemployment rate, the stochastic search method successfully selects lag one as the time delay and five best models from more than 4000 choices. Copyright © 2003 John Wiley & Sons, Ltd.