基于小波包Bark子带方差的端点检测算法

传统的端点检测方法大多数抗噪性不好,基于能量和短时过零率的双参数双门限端点检测在静音状态下效果较好,但是在噪声环境中性能下降.针对这个问题,使用小波包变换把信号分解成17个Bark子带,求出平均方差值,然后采用单参数双门限方法进行端点检测.实验证明,即使在-2dB的噪声环境下,该方法仍然能取得较好的端点检测效果.     

基于多窗口分析的语音检测方法

针对低信噪比条件下的语音信号检测性能差的问题,提出了一种基于多窗口时频图的语音活动检测方法.首先,基于多窗口的时频分析计算得到语音信号的时频图,根据语音信号与背景噪声的特征差构造语音测试统计特征.其次,采用动态的双门限处理进行初步检测,在此基础上通过K均值聚类得到全局的双门限值.最后,根据序贯判决的思想进行检测得到该方...     

基于小波分析的红外弱小目标检测算法

针对红外弱小目标检测需求,根据红外弱小目标图像特性及其小波分析特性,提出了一种基于小波分析的红外弱小目标检测算法。算法首先对红外弱小目标图像进行小波分解;然后置低频小波系数为零去除背景,阈值化高频小波系数滤除噪声,自适应子带增强加强目标能量;最后进行小波逆变换并进行自适应阈值分割。实验结果表明,提出的算法速度快、抑制噪声的能力强。     

Adaptive Multi-user Detection Based on Convolution Wavelet Packet Transformation

为提高DS-CDMA多用户系统检测的效率,提出了基于卷积小波包变换的自适应算法.理论分析和仿真结果表明.该算法收敛速度快,且计算量增加较少,是一种高效的自适应检测算法.     

适用于认知无线电网络典型场景的空闲频谱检测方法(英文)

针对认知无线网络若干典型场景,提出一种新的空闲频谱检测方法以提高其检测概率. 通过消除空间虚警对频谱感知的影响,得到认知用户在路径损耗和多径衰落作用时的空闲频谱检测概率,同时得到多用户合作检测以及单用户在宽带环境检测时的空闲频谱检测概率并进行对比. 理论分析和仿真结果表明: 所提方法的空闲频谱检测概率与采样次数以及检测区域面积成反比; 采用"与"融合规则进行多用户检测时效果好于单用户检测,采用"或"融合规则时则相反;瑞利衰落会使检测概率进一步减小,而增加带宽则会使其大大提高.     

基于多点随机搜索的自适应随机共振信号检测系统

提出了一种基于多点随机搜索算法的自适应随机共振系统模型,并以LabVIEW为平台开发了自适应随机共振微弱信号检测系统.该检测系统以典型非线性双稳系统为信号处理核心,以系统输出信噪比为优化目标函数,采用多点随机搜索算法自适应调整系统结构参数,使系统处于随机共振最佳状态,并获取微弱信号的频率特征值.利用该系统可测试各种系统参数及高斯噪声对随机共振的影响.实验结果表明,该系统检测效果良好,具有较好的应用价值.     

鲁棒的广告视频检测技术研究

将基于自适应双阈值镜头检测算法与电视节目的音频特征相结合,本文提出了一个鲁棒的电视节目广告片段检测算法.首先采用将自适应双阈值镜头检测算法分割出电视节目和广告视频镜头.为了提高镜头边界检测的准确率,本文提出将音频切变信息融合到镜头边界检测算法中.最后利用非对称AdaBaost算法对镜头进行分类,得到无广告视频的完整电视节目.实验结果表明此广告视频检测技术具有实用性.     

一种新的模糊边缘检测算法

基于信息论中最大熵原理 ,提出了一种新的模糊边缘检测算法 .首先介绍了模糊概率、用条件概率与条件熵定义模糊划分熵的概念以及模糊划分的原理 .算法利用了自然划分以及梯度图像模糊划分的关系 ,在条件概率与模糊划分熵的基础上 ,通过最大模糊熵原则实现图像分割中最优阈值的自动提取 ,从而实现图像的边缘检测 .对不同测试图像的边缘检测结果进行比较 ,表明了该算法的有效性 .     

基于内容优化双边滤波的运动自适应算法

本文提出了一种基于内容的优化双边滤波运动自适应去隔行算法.该算法在传统运动自适应算法的基础上,利用双边滤波改进了视频中的动静检测方法,改善了视频插值点的运动状态,能较好的识别视频中的动静区域,具有较好的抗噪声能力及静态物体边缘保持能力,并能够根据图像的内容,自适应地调整运动静态权重,达到较好的去隔行效果.     

基于危险免疫模型的入侵检测算法研究

本文提出的基于危险免疫模型(DIM)的入侵检测算法是借鉴了生物免疫学危险模型中的相关概念,引入了危险区域和危险信号等新型处理机制,对入侵数据包进行自适应学习.实验证明,该算法具有强于传统方法的学习能力以及识别效果,且具有更低的算法时间复杂度.     

认知无线电频谱感知算法研究

随着信息社会经济的快速发展,人们对移动通信、宽带无线接入的需求不断增长,无线频谱资源越来越匮乏,频谱指配越来越困难。认知无线电技术接入灵活,能够大大提高频谱的利用率,当前被认为是解决上述问题的最佳方案。无线频谱感知技术是认知无线电的基础,文章对主用户的发射端、接收端的频谱感知算法,基于小波基的多分辨率宽带信号频谱感知算法,多节点协同感知算法进行了研究,分析对比给出了各种算法的优缺点。     

软判决协作频谱感知的最优判决门限(英文)

为了获得认知无线电系统更高的频谱利用效率,基于最小总错误概率准则推导了软判决协作频谱感知最优判决门限的闭合表达式,并且分析了各种频谱感知参数对最优判决门限的影响.理论分析表明,所提出的最优门限可以获得虚警概率和漏检概率2种性能指标的折中.从仿真结果可以看出,平均信噪比和软判决方案对最优判决门限影响较大,而样本数量对最优的判决门限几乎无影响.对于MRC和MDC两种软判决方案,随着协作用户数量的增加,最优判决门限值随之增加并且趋近于某一极限值.而对于EGC软判决方案,协作用户数对其最优门限值影响很小.     

Optimization of threshold for local spectrum sensing with energy detector

Spectrum sensing is the first step of cognitive radio (CR). In this area, previous researches mostly consider distributed local nodes which are under identical channel conditions, hence uniform and fixed detection threshold is set with energy detector. However, the distributions of nodes in real environments are not quite the same. In this paper, the optimal threshold to minimize the total detection error over additive white Gaussion noise (AWGN) channel is derived firstly. Then the dynamic threshold scheme is proposed to reduce the average total detection error. Simulations have shown that, with this scheme, sensing performance is improved.     

基于在线单类支持向量机的自适应语音活动检测

针对非平稳噪声环境下的语音活动检测问题,提出了基于在线单类SVM的自适应语音活动检测算法。该算法采用单类SVM对多种特征信息进行在线学习与综合,为非平稳背景噪声建模,并采用双层决策机制,能有效提高语音活动检测的稳健性。在语音识别系统中的实验结果表明,算法在多种噪声环境和信噪比条件下有效,并明显提高了在非平稳噪声环境下的识别率。     

多频带UWB通信系统中低复杂度迭代差分译码算法

相对于相干检测,由于在收发端不需要信道状态信息,非相干UWB通信在信噪比方面会有近3dB的性能损失.为了克服这一性能差距,提出了一种有效的基于多频带UWB系统的差分编译码方案.该方案在发射端使用2个并行级联的递归酉差分空频编码器对数据进行编码.接收端的2个分量译码器通过互相交换软度量值对数据进行译码.为了降低接收机的计算复杂度,给出一种只使用转移概率计算信息比特似然比的译码算法.仿真结果表明,在较少迭代次数下,算法性能远优于传统非相干检测,在高信噪比时,其性能甚至超过了相干检测.     

A cross-layer design approach on spectrum allocation and resource scheduling in cognitive PMP networks

We propose the spectrum allocation and resource scheduling algorithms in cognitive point to multipoint （PMP） networks with rapid changes of spectrum opportunities and present a media access control （MAC） protocol based on these algorithms. The objective of spectrum allocation is to make efficient use of the spectrum while maintaining the transceiver synchronization on frequency and time in the network. The objective of resource scheduling is to guarantee the quality of service （QoS） requirements of different kinds of connections and to minimize the total energy consumption in the network as well. By sensing only a small set of possible channels in each slot based on the state transition probability of each channel, our spectrum allocation algorithm achieves high spectrum efficiency in the network. The resource scheduling problem is divided into three sub problems and we derive optimal solutions to these problems by greedy algorithm and convex optimization. The simulation results show that our algorithm can make efficient use of the spectrum and the network resources at a cost of low computational complexity.     

Joint compressive spectrum sensing scheme in wideband cognitive radio networks

In this paper, a distributed compressive spectrum sensing scheme in wideband cognitive radio networks is investigated. An analog-to-information converters (AIC) RF front-end sampling structure is proposed which use parallel low rate analog to digital conversions (ADCs) and fewer storage units for wideband spectrum signal sampling. The proposed scheme uses multiple low rate congitive radios (CRs) collecting compressed samples through AICs distritbutedly and recover the signal spectrum jointly. A general joint sparsity model is defined in this scenario, along with a universal recovery algorithm based on simultaneous orthogonal matching pursuit (S-OMP). Numerical simulations show this algorithm outperforms current existing algorithms under this model and works competently under other existing models.     

Implementation of a Novel Algorithm on Acoustic Doppler Current Profiler Signal Processing System＊

Acoustic Doppler current profiler （ADCP） uses acoustic energy directed along narrow beams for current measurement. In conventional method, the quantity of sampling affects the precision of fast Fourier transform （FFT） algorithm, and the algorithm needs a large amount of data to process. A novel frequency estimator.enhanced least mean square （ELMS） algorithm for a single complex sinusoid in complex white Gaussian noise, is proposed in ADCP system. As sampling frequency equals 120 krad/s and the sampling number equals 240. the minimum resolving is 0. 5 krad/s. All variances keep 11.11%. ELMS algorithm needs less data than FFT. And the robust algorithm can estimate the spectrum true value to 99.9% when the signal to noise ratio （SNR） is equal to 0 dB. Experiments prove that the estimation values will diverge much from the ideal when SNR is less than -6 dB.     

Reputation-based linear cooperation for spectrum sensing in cognitive radio networks

We propose a reputation-based cooperative spectrum sensing scheme in cognitive radio （CR） networks to solve the uncertainty resulting from the multipath fading and shadowing effect. In the proposed scheme, each cooperative CR user has a reputation degree that is initialized and adjusted by the central controller, and used to weight the sensing result from the corre- sponding CR user in the linear fusion process at the central controller. A simple method for adjusting the reputation degree of CR users is also presented. We analyzed and evaluated the detection performance of the reputation-based cooperative spectrum sensing scheme. Simulation results showed that our proposed scheme alleviates the problem of corrupted detection resulting from destructive channel conditions between the primary transmitter and the CR user. The performance of our proposed scheme was improved compared to the average-based linear cooperation scheme, and was similar to that of the optimal linear cooperation scheme with feasible computational complexity. Moreover, our proposed scheme does not require knowledge of channel statistics.     

基于波谱特征曲线法的遥感图像海岸线提取

本文利用遥感图像的反射波谱信息,提出了海岸线提取的一种方法。首先,根据遥感图像中水体独特的反射波谱特征,提出了以特征曲线法来进行水陆分离,其核心是基于地物波谱的相似度,以水体反射波谱曲线作为中心判据,当目标像元的特征曲线符合中心判据时,将目标像元分类为水体,反之为非水体,从而实现水陆分离。中心判据由水体波谱在遥感图像各波段的分布特征来确定。然后利用形态学方法,对水陆分离后的图像进行海岸线提取。本文以Quick Bird图像和IKONOS图像为例,利用ENVI软件编程,实现了对归一化后的遥感图像的海岸线提取。结果表明所获取的海岸线连续性好、信噪比高,算法简单且适用性强。进一步研究自适应获取中心判据的方法,可使该算法用于工程化运算。