帧长和信道预测对自适应调制系统性能的影响

该文主要分析了在自适应调制系统中,帧长自适应和信道预测对系统性能的影响。推导了信道预测和没有信道预测的自适应调制系统的频谱效率公式,分析结果表明对于自适应调制系统,信道预测的系统频谱效率是最优的,非信道预测系统根据信道情况选择最优帧长可以获得该系统的最优系统频谱效率,但它是低于信道预测的频谱效率的,而且是随多普勒频率的增大而逐渐减小的。     

时变参数辨识方法在导弹自动驾驶仪中的应用

研究适合导弹自适应自动驾驶仪设计中对于参数快速变化的有效的辨识方法,从几种时变参数辨识方法的研究着手,经过适当的修改和组合,得出适用的辨识方法。通过从理论分析到微机仿真等一系列工作,证明了这一辨识方法能够较好跟踪导弹气动参数的变化。     

自适应有源噪声控制的滤波-LMAD算法

本文研究了稳定非高斯环境下的自适应有源噪声控制问题，提出了滤波－ＬＭＡＤ（ｌｅａｓｔｍｅａｎａｂｓｏｌｕｔｅｄｅｖｉａｔｉｏｎ）算法及归一化滤波－ＬＭＡＤ算法，仿真结果表明，与常用的滤波－ＬＭＳ算法和归－化滤波－ＬＭＳ算法相比，本文提出了算法收敛速度更快。     

稀布阵综合脉冲孔径雷达旁瓣对消性能分析

定量分析了阵列孔径、干扰信号带宽、通道幅相误差以及Ａ／Ｄ变换器的量化噪声对大型稀布圆形阵列天线干扰对消效果的影响，介绍了稀布阵综合脉冲孔径雷达（ＳＩＡＲ）采用抽头延迟线以提高干扰对消性能的方法，并给出了数值计算与计算机模拟结果。     

自适应阵对角线加载研究

本文分析了对角线加载对自适应阵性能的影响，提出了加载门限的概念，以及加载门限的计算公式，为加载量的选取提供了方法和依据，并将加载研究的结果加以推广，提出了有效的ＬＳ自适应波束形成算法的非零初始化方法。     

一种有限元自适应剖分的误差计算方法的实现

本文在总结有限元自适应剖分的误差计算方法的基础上,提出了一种新的误差定义,并通过计算实例证明其可行性。文中还定性地讨论了预置的误差控制值ε对计算效果的影响。     

Comfort criteria for passively cooled buildings a pascool task

The application of passive cooling techniques to buildings in warm climates creates the need for appropriate comfort criteria. Conventional comfort criteria, usually based upon laboratory experiments, seem to be unnecessarily severe. The paper describes preliminary findings of the PASCOOL Thermal Comfort task which, responding to renewed interest in behavioural aspets of thermal comfort, sets out to establish appropriate limits by field studies and theoretical considerations.     

Joint face and head tracking inside multi-camera smart rooms

The paper introduces a novel detection and tracking system that provides both frame-view and world-coordinate human location information, based on video from multiple synchronized and calibrated cameras with overlapping fields of view. The system is developed and evaluated for the specific scenario of a seminar lecturer presenting in front of an audience inside a “smart room”, its aim being to track the lecturer’s head centroid in the three-dimensional (3D) space and also yield two-dimensional (2D) face information in the available camera views. The proposed approach is primarily based on a statistical appearance model of human faces by means of well-known AdaBoost-like face detectors, extended to address the head pose variation observed in the smart room scenario of interest. The appearance module is complemented by two novel components and assisted by a simple tracking drift detection mechanism. The first component of interest is the initialization module, which employs a spatio-temporal dynamic programming approach with appropriate penalty functions to obtain optimal 3D location hypotheses. The second is an adaptive subspace learning based 2D tracking scheme with a novel forgetting mechanism, introduced to reduce tracking drift and increase robustness. System performance is benchmarked on an extensive database of realistic human interaction in the lecture smart room scenario, collected as part of the European integrated project “CHIL”. The system consistently achieves excellent tracking precision, with a 3D mean tracking error of less than 16 cm, and is demonstrated to outperform four alternative tracking schemes. Furthermore, the proposed system performs relatively well in detecting frontal and near-frontal faces in the available frame views. This work was performed while Zhenqiu Zhang was on a summer internship with the Human Language Technology Department at the IBM T.J. Watson Research Center.     

强噪声背景下确定性谐波信号的模糊滤波

文章提出了一种在强背景噪声环境下对被淹没的谐波信号进行模糊滤波，从而恢复微弱目标信号的方法。在MATLAB环境下，先利用相干平均法，除去被测信号中的随机白噪声，对于有色噪声运用自适应神经模糊推理系统（ANFIS）的方法，对被测信号进行模糊滤波，在较低信噪比下，能较好的恢复出原始微弱信号。