爆炸物检测中微弱NQR信号的处理

介绍了用核四极矩共振技术检测爆炸物品的原理及检测过程中信号的处理方法。根据NQR测量中接收信号极其微弱的特点,针对以数字累加技术处理NQR信号的常规方法,提出了利用相关检测的方法来处理核四极矩共振（NQR）信号,该方法可以更有效地提高信噪比,并消除随机噪声和外界干扰对接收信号的干扰,从而提高了检测微弱NQR信号的准确性。     

基于奇异值分解的NQR信号去噪分析

核四极矩共振方法探测系统可用于炸药等危险品的检测,通常它们的核四极矩共振信号十分微弱,探测系统的输出信噪比很低,大大增加了检测的困难,文中基于奇异值分解,叙述了一种有效的去噪方法,从而有效地提高了系统的输出信噪比.     

一种自适应去除振铃滤波新算法

振铃效应严重地影响了复原图像质量,在此针对MEPG-4中的去振铃滤波方法,提出一种新的去振铃滤波算法,既能有效消除振铃效应又能充分保护图像的边缘。算法首先找出边缘区域和非边缘区域,然后根据振铃效应产生的原因和现象,采用中值滤波器对图像进行自适应滤波,以去除振铃效应。实验结果表明,这里的滤波算法相对于MEPG-4中的去振铃滤波方法,能更加有效地去除振铃效应,并且大大提高了图像的主客观质量。     

基于自适应滤波的微弱信号测量方法研究

本文介绍了几种常见微弱信号检测方法的优缺点,筛选出更适用于无线电监测工作的自适应滤波的微弱信号测量办法,简要分析了自适应滤波的原理和特点,并进行了仿真实验.理论实验表明,该测量方法可以有效除模拟广播信号和某些数字信号的噪声,达到突出微弱信号的目的 .     

基于神经网络的自适应滤波技术

本文在Ｈｏｐｆｉｅｌｄ神经网络和ＴＨ线性优化网络的茂盛耻，提出了自适应滤波算法的神经网络实现，理论和计算机模拟均表明该算法的神经网络硬件实现，将大大提高自适应滤波器的时效性。     

基于改进粒子滤波和自适应融合的目标跟踪

针对复杂环境下视频目标跟踪精确度低的问题,提 出了一种基于混合迭代无迹粒子滤波(HI-UPF)和关联系数自 适应融合的目标跟踪算法。首先采用统计线性回归的方法对无迹变换进行优化,提出了HI- UPF,不 仅提升了滤波精度,而且有效降低了算法的时间消耗;其次基于关联系数,采用一种自适应 融合方法,实现了加性 融合和乘性融合的自适应切换,并根据关联系数提出一种改进的自适应加性融合方法。仿真 实验表明,本文方法对 于复杂条件下的目标跟踪具有较高的精度和较强的鲁棒性。     

基于自适应滤波处理的网络入侵监测系统设计

目前设计的网络入侵监测系统对于入侵信息的漏报率较高,准确率较低。为了解决上述问题,引入自适应滤波处理技术,设计了一种新的网络入侵监测系统。系统硬件通过滤波器增强信息过滤能力,利用数据采集器采集数据,采用处理器和监测器分析数据信息。应用自适应滤波技术对信息进行检测、过滤,完成软件工作流程。实验结果表明,基于自适应滤波处理的网络入侵监测系统能够有效降低系统的漏报率,提高监测结果准确率。     

多干扰成分的非稳态信号自适应滤波技术

信号在受到色噪声和白噪声混合干扰下产生非稳态突变,导致信号的检测识别性能下降,需要进行滤波降噪处理,提出一种基于格型陷波器级联的非稳态信号自适应滤波技术.构建直接性陷波器,采用高阶检波技术进行滤波器级联设计,构建二阶格型陷波器,根据滤波器传输函数的幅度和相位响应实现线谱增强和噪声抵消,实现多干扰成分的非稳态信号自适应滤波改进.仿真结果表明,采用该滤波算法构建信号滤波器,能有效去除信号中的干扰噪声成分,提高输出信噪比.     

基于多相滤波的ILS信号的数字正交变换技术

为了尽可能多地用软件来实现仪表着陆系统（ILS）接收机的信号处理,需要对导航信号进行数字化,而基于多相滤波的数字正交变换无需正交本振,结构上也更适用于实时处理系统。介绍了ILS的工作原理及信号体制,研究了基于多相滤波的ILS信号的数字正交变换技术,通过MATLAB仿真验证了设计的可行性。     

一种基于PCNN算法的图像选点滤波方法

提出了一种新的基于脉冲耦合神经网络算法的图像选点滤波方法,首先介绍了脉冲耦合神经网络算法模型,分析了噪声的特点。然后提出新的算法：用脉冲耦合神经网络构造图像像素点火时间矩阵,根据时间矩阵判别该点应采取怎样的滤波算法。最后通过图像质量评价方法对实验结果作了分析,结果证明该方法有效可靠,能够抑制高斯噪声和脉冲噪声。     

一种基于自适应滤波的语音降噪方法研究

分析和研究自适应滤波和小波变换法的原理及方法,提出了一种新的综合使用自适应滤波和小波变换法的语音降噪方法。该方法首先用仿生小波变换法对带噪声的语音信号进行小波分解,将小渡变换法分离出来的噪声信号作为自适应滤波器的输入。最后选择用最小均方误差（LMS）的自适应算法对带噪声语音信号进行降噪处理,实现了信噪分离,去除语音信号中的噪声信号。实验结果表明,该方法对语音信号有较为明显的降噪效果。     

Two-dimensional adaptive filtering based on projection algorithm

In this paper, we propose a two-dimensional (2-D) projection algorithm by which filter coefficients can be updated both along the horizontal and the vertical directions on a 2-D plane. Some basic properties of the algorithm are derived. In order to compare with other 2-D adaptive algorithms, it is applied to the identification of 2-D systems with stationary or nonstationary characteristics as well as the reduction of image noise. Results show that the proposed 2-D Modified Projection Algorithm (MPA) achieves good performance for both cases.     

A direction set based algorithm for adaptive filtering

A new algorithm is developed for adaptive filtering applications. This algorithm is based on a direction set method and has a computational complexity of O(N) for each update of the system. The method exploits the structure of the objective function and maintains a set of near-conjugate directions with respect to the Hessian. This algorithm has a rapid rate of convergence that is comparable with that of the well-known RLS method. The performance of the algorithm is illustrated with adaptive filtering applications     

Blind adaptive multiuser detection based on Kalman filtering

Although several Kalman filtering algorithms have been presented for adaptive multiuser detection, none is "blind" due to requiring training data sequences and/or more knowledge than the spreading waveform and delay of the desired user. This paper proposes a novel blind adaptive multiuser detector based on Kalman filtering and compares it with previously published LMS and RLS algorithms for blind adaptive multiuser detection. It is shown that the steady-state excess output energy of the Kalman filtering algorithm is identically zero for a stationary environment. Simulation results show the effectiveness of the new Kalman filtering algorithm     

一种基于期望模型的自适应Singer模型滤波算法

针对使用固定模型滤波算法跟踪机动目标时滤波精度依赖于模型固有参数的问题,提出了一种基于期望模型的自适应Singer模型滤波算法。首先利用3组代表不同机动强弱的典型Singer模型组成基础模型集合,然后通过实时计算目标综合残差确定目标机动等级,根据目标机动等级的变化来生成期望模型,并实时扩充基础模型集合进行交互式多模型（Interacting Multiple Model,IMM）滤波。该算法降低了对基础模型选取的依赖性,具有更好的环境适应性,在目标不同机动状态下都能进行准确跟踪。     

基于GSC框架降秩自适应滤波算法研究

基于对自适应滤波算法的研究可以得出,GSC(Generalized Sidelobe Canceller)框架是所有降秩滤波算法的统一基础模型,通过对GSC一般结构的降秩模型的研究。文中提出了3种能够改善一般结构结果的优化模型,PC(Prin-ciple Component)主分量算法、CS(Cross Spectrum)交叉谱算法、MWF(Mutistage Wiener Filter)多级维纳滤波器。这三种方法都是基于特征子空间截断的方法。通过对降秩矩阵T的特征值分解和重新构造,大大降低了自由度和工程运算量。该两种方法在实际应用中具有更优的实时性。仿真结果证明了提出的基于广义旁瓣相消的降秩自适应波束形成算法具有良好的降低自由度和波束形成性能,验证了算法的有效性。     

Fast adaptive filtering algorithm based on exponentially weightedleast-square errors

The linearly filtered gradient least mean square algorithm is reformulated using exponentially weighted least-square errors, and a partially filtered gradient LMS algorithm is proposed as a variant. It is shown that the proposed algorithm is superior in terms of convergence and tracking capability compared to the LMS and FGLMS algorithms     

An adaptive background reconstruction algorithm based on inertial filtering

To improve the detecting effects of moving objects, an adaptive background reconstruction algorithm based on inertial filtering is proposed in this paper. According to different properties of the moving foreground and ever-changing background, the current frame is added to the background with a specific weight value. So the background can not only keep steady, but also be reconstructed at a specific speed. Experimental results show that the algorithm can reconstruct the background quickly and effectively whenever the background changes slowly or suddenly, or the background is mixed with moving foreground, and it can improve the veracity and robustness of objects detection effectively.     

A new adaptive filtering scheme based on wavelet transform

Based on the scale function representation for a function in L ²(R), a new wavelet transform based adaptive system identification scheme is proposed. It can reduce the amount of computation by exploiting the decimation properties and keep the advantage of quasi-orthogonal transform of the discrete wavelet transform (DWT). The issue has been supported by computer simulations. Supported by the National Natural Science Foundation of China, no.69672039