共查询到20条相似文献,搜索用时 468 毫秒
1.
2.
盲源分离是指在没有任何先验知识的前提下,从观测到的多个混合信号中提取或分离出未知源信号的过程.本文主要探讨了基于独立分量分析的盲源分离自然梯度算法及活动函数的选取,并利用该算法实现了5路混合信号和3路自然语音信号的分离,最后在Mat-lab2008下进行了仿真验证.结果表明该算法能够有效实现语音信号的分离. 相似文献
3.
4.
5.
针对现有的独立成分分析法分离混合混沌信号精度不理想的问题,提出了一种新的混沌信号盲分离方法。该方法以求解最优解混矩阵为目标,利用峭度构造目标函数,将混沌信号的盲源分离转化为一个优化问题,并用萤火虫算法求解。同时,通过预白化和正交矩阵的参数化表示降低优化问题的维数,能有效提高分离精度。仿真结果表明,无论是处理混合的混沌映射信号还是混合的混沌流信号,该方法都能快速收敛,并且其分离精度在各项实验中都优于独立成分分析法等现有的盲源分离方法。 相似文献
6.
7.
8.
对于含噪声情况下多个源信号卷积混合盲分离,由于混合矩阵比较复杂,分
离算法会出现迭代次数增加、收敛速度变慢等问题。在对多信号卷积混合进行合理简
化的基础上,提出一种以四阶累积量为独立准则的多信号卷积混合的新的时域盲源分离算法
。由于采用高阶累积量为独立准则,该算法对高斯噪声具有良好的抑制作用,改善了信噪比
。
其次,算法也建立了步长因子的选取与二次残差之间的非线性函数关系,使得算法既获得了
较
快的收敛速度,也得到较高的分离精度。仿真数据表明提出的算法对于多个源信号卷积
混合具有良好的分离效果。 相似文献
9.
10.
本文提出了一种新的后非线性混合盲信号分离算法.现存算法大多需要额外的附加源信号信息,才能实现信号的分离,使盲分离变成了半盲分离.鉴于此,本文提出了一种不需要任何附加信息的全盲分离算法.首先,通过微分变换将后非线性混合模型变换成形式如同线性瞬时混合模型的形式,并论证了源信号的微分形式保留了源信号的统计特征.这样,就使非线性问题得到大大简化.其次,利用信号的相火特性建立目标函数及递推方式,用LMS算法使目标函数达到最小值,从而实现了盲信号分离的目的.最后,通过计算机仿真试验验证了本文算法的可行性和有效性.与现存算法相比,本文算法计算量小,收敛速度快,实时性好,实现了全盲分离. 相似文献
11.
针对星载船舶自动识别系统( AIS )的含噪复值信号盲分离算法分离效果不佳的问题,提出了改进的复值快速独立分量分析算法( FastICA)。该改进算法针对混合信号数目大于源信号数目的超定情况,对含噪混合信号的协方差矩阵进行特征值分解,利用其噪声对应的几个较小特征值估计噪声方差,修正白化矩阵,再应用Huber M估计函数优化该算法的目标函数。实验结果表明,运用该算法信号均方误差( SMSE)变小,信干比( SIR)变大,提高了信号的分离性能;同时,优化后的目标函数使算法具有良好的稳健性。 相似文献
12.
本文回顾了一些最新的求解非线性盲源分离问题的神经网络算法。其中,对于多层感知器网络、径向基函数网络、多项式网络尤其关注。为了从非线性混叠信号中分解出唯一的源信号解,需要给神经网络加上一系列的限制。提出了三种结构限制的独立分量分析混合模型.接着讨论了加在源自交叉熵的原始代价函数上的额外的信号约束。 相似文献
13.
针对非协作通信中成对载波多址(Paired Carrier Multiple Acess,PCMA)信号的盲分离问题,提出了一种基于独立分量分析(Independent component analysis,ICA)的单通道盲分离算法。首先对接收到的单路PCMA信号进行参数估计得到其残余载波频率,再对其处理得到两路基带混合信号,最后利用ICA算法分离出源基带信号。该算法在未知两个卫星地面站发送信号的情况下,从接收到的PCMA信号中恢复出两路源基带信号。仿真实验表明,本文算法在信噪比为-10dB时仍具有良好的分离效果,两路基带信号的波形相似系数可分别达到0.94与0.86以上。 相似文献
14.
Matrix-Group Algorithm via Improved Whitening Process for Extracting Statistically Independent Sources From Array Signals 总被引:3,自引:0,他引:3
Da-Zheng Feng Wei Xing Zheng Andrzej Cichocki 《Signal Processing, IEEE Transactions on》2007,55(3):962-977
This paper addresses the problem of blind separation of multiple independent sources from observed array output signals. The main contributions in this paper include an improved whitening scheme for estimation of signal subspace, a novel biquadratic contrast function for extraction of independent sources, and an efficient alterative method for joint implementation of a set of approximate diagonalization-structural matrices. Specifically, an improved whitening scheme is first developed by estimating the signal subspace jointly from a set of diagonalization-structural matrices based on the proposed cyclic maximizer of an interesting cost function. Moreover, the globally asymptotical convergence of the proposed cyclic maximizer is analyzed and proved. Next, a novel biquadratic contrast function is proposed for extracting one single independent component from a slice matrix group of any order cumulant of the array signals in the presence of temporally white noise. A fast fixed-point algorithm that is a cyclic minimizer is constructed for searching a minimum point of the proposed contrast function. The globally asymptotical convergence of the proposed fixed-point algorithm is analyzed. Then, multiple independent components are obtained by using repeatedly the proposed fixed-point algorithm for extracting one single independent component, and the orthogonality among them is achieved by the well-known QR factorization. The performance of the proposed algorithms is illustrated by simulation results and is compared with three related blind source separation algorithms 相似文献
15.
16.
17.
基于峭度的盲分离在通信信号盲侦察中的应用 总被引:3,自引:2,他引:1
为实现复杂多信号环境下的通信信号侦察,采用一种新的盲侦察技术,即运用盲源分离算法,在没有任何先验知识的情况下分离出源信号,然后对分离的各个信号进行后续处理。提出一种改进的基于峭度的盲分离算法,可以自适应地确定激活函数。将其应用在通信信号盲侦察中,可以实现对任意源信号进行盲分离,而不管它是超高斯还是亚高斯信号。选择超高斯和亚高斯混合通信信号进行了仿真实验,结果验证了该算法的有效性。 相似文献
18.
Method for eliminating mode mixing of empirical mode decomposition based on the revised blind source separation 总被引:2,自引:0,他引:2
Since mode mixing of empirical mode decomposition (EMD) is mainly caused by the intermittence and noise, we propose a novel method to eliminate mode mixing of EMD based on the revised blind source separation. To this aim, an optimal morphological filter is employed to eliminate the noise. As a result, the component of mode mixing caused by noise is suppressed. Furthermore, the de-noised signal is decomposed into different intrinsic mode function (IMF) components through the EMD algorithm. Since it is impossible to apply blind source separation to a single channel signal directly, the IMF component, which has mode mixing is chosen and reconstructed in the phase space. Following that, the equivalent hypothetical signals are obtained. Finally, an improved fixed-point algorithm based on independent component analysis (ICA) is introduced to separate the overlapping components. The analysis of simulation and practical application demonstrates that our proposed method can effectively tackle the mode mixing problem of EMD. 相似文献
19.