共查询到20条相似文献,搜索用时 296 毫秒
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Hai Huyen Dam Nordholm S. Siow Yong Low Cantoni A. 《Signal Processing, IEEE Transactions on》2007,55(8):4198-4207
A method that significantly improves the convergence rate of the gradient-based blind signal separation (BSS) algorithm for convolutive mixtures is proposed. The proposed approach is based on the steepest descent algorithm suitable for constrained BSS problems, where the constraints are included to ease the permutation effects associated with the convolutive mixtures. In addition, the method is realized using a modified golden search method plus parabolic interpolation, and this allows the optimum step size to be determined with only a few calculations of the cost function. Evaluation of the proposed procedure in simulated environments and in a real room environment shows that the proposed method results in significantly faster convergence for the BSS when compared with a fixed step-size gradient-based algorithm. In addition, for blind signal extraction where only a main speech source is desired, a combined scheme consisting of the proposed BSS and a postprocessor, such as an adaptive noise canceller, offers impressive noise suppression levels while maintaining low-target signal distortion levels. 相似文献
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The linear mixing model has been considered previously in most of the researches which are devoted to the blind source separation (BSS) problem. In practice, a more realistic BSS mixing model should be the non-linear one. In this paper, we propose a non-linear BSS method, in which a two-layer perceptron network is employed as the separating system to separate sources from observed non-linear mixture signals. The learning rules for the parameters of the separating system are derived based on the minimum mutual information criterion with conjugate gradient algorithm. Instead of choosing a proper non-linear functions empirically, the adaptive kernel density estimation is used in order to estimate the probability density functions and their derivatives of the separated signals. As a result, the score function of the perceptron’s outputs can be estimated directly. Simulations show good performance of the proposed non-linear BSS algorithm. 相似文献
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Siow Yong Low Cedric Ka-Fai Yiu Sven Nordholm 《International Journal of Electronics》2013,100(9):1583-1593
The aim of this paper was to provide a derivation to explain the performance of the second-order-based blind signal separation (BSS) in reverberant environments. In particular, the second-order-based BSS algorithm, which exploits non-stationarity of the input signals, is investigated. The derivation provides a quantitative link between the reverberation parameter of the environment with the cost function of the BSS. Importantly, the theoretical finding complements existing literature on the interpretation of BSS and provides incremental insight to its performance. 相似文献
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Frdric Vrins Dinh-Tuan Pham Michel Verleysen 《IEEE transactions on information theory / Professional Technical Group on Information Theory》2007,53(3):1030-1042
In this paper, both non-mixing and mixing local minima of the entropy are analyzed from the viewpoint of blind source separation (BSS); they correspond respectively to acceptable and spurious solutions of the BSS problem. The contribution of this work is twofold. First, a Taylor development is used to show that the exact output entropy cost function has a non-mixing minimum when this output is proportional to any of the non-Gaussian sources, and not only when the output is proportional to the lowest entropic source. Second, in order to prove that mixing entropy minima exist when the source densities are strongly multimodal, an entropy approximator is proposed. The latter has the major advantage that an error bound can be provided. Even if this approximator (and the associated bound) is used here in the BSS context, it can be applied for estimating the entropy of any random variable with multimodal density 相似文献
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The problem of multiuser interference cancellation in wireless cellularcommunication systems accepts a blind source separation (BSS) model. Thepresent contribution studies the closed-form solutions to BSS in thereal-mixture case. Connections among a number of seemingly disparate methodsare unveiled, new procedures are put forward, and their asymptotic(large-sample) performance is analyzed. Simulation experiments illustrate andvalidate the theoretical results. Altogether, a unifying generic framework forclosed-form BSS methods is developed. 相似文献
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Direct-sequence spread-spectrum (DSSS)/code division multiple access (CDMA) transmissions are now widely used for secure communications
and multiple access. They can be transmitted at a low signal-to-noise ratio, and have a low probability of interception and
capture. How to obtain the original users' signal in a noncooperative context or estimate the spreading sequence in blind
conditions is a very difficult problem. Most of the signal sources are assumed to be instantaneous mixtures. In fact, the
received CDMA signals are linearly convoluted. A more complicated blind source separation (BSS) algorithm is required to achieve
better source separation. In this paper, a new BSS algorithm is proposed for separating linearly convolved signals in CDMA
systems when the mixture coefficients of the signal and channel response are totally unknown, but some knowledge about the
temporal model does exist. This algorithm is based on minimizing the squared cross-output-channel-correlation criterion. The
simulation results show the effectiveness of the algorithm in the blind detection of DS-CDMA signals. 相似文献
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Hong-Guang Ma Qin-Bo Jiang Zhi-Qiang Liu Gang Liu Zhi-Yuan Ma 《Signal processing》2010,90(12):3232-3241
The blind separation of single-channel signal is one of the most important aspects in many fields. Our research is carried out to develop a blind separation method of single-channel signal, in which the singular spectrum analysis (SSA) and blind source separation (BSS) techniques are jointly used, i.e. the single-channel signal is firstly changed into pseudo-MIMO (multi-input and multi-output) mode, and then each source signal is separated via a fast BSS algorithm. A signal preprocessing procedure, which is mainly focused on testing the nonstationarity of single-channel signal, is conducted before the operations of mixed signal transform and separation. In this research, the approach of heuristic segmentation of a nonstationary time-series is proposed. Throughout the experiment, the effectiveness of the proposed method is validated with a data set taken from a digital wideband receiver in an outdoor test. Then, a comparison is made between the proposed method and the Hilbert–Huang transform (HHT)-based signal separation method. The advantage of the proposed method is exhibited. 相似文献
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Bohm M Stadlthanner K Gruber P Theis FJ Lang EW Tome AM Teixeira AR Gronwald W Kalbitzer HR 《IEEE transactions on bio-medical engineering》2006,53(5):810-820
In this paper, an automatic assignment tool, called BSS-AutoAssign,for artifact-related decorrelated components within a second-order blind source separation (BSS) is presented. The latter is based on the recently proposed algorithm dAMUSE, which provides an elegant solution to both the BSS and the denoising problem simultaneously. BSS-AutoAssign uses a local principal component analysis (PCA)to approximate the artifact signal and defines a suitable cost function which is optimized using simulated annealing. The algorithms dAMUSE plus BSS-AutoAssign are illustrated by applying them to the separation of water artifacts from two-dimensional nuclear overhauser enhancement (2-D NOESY)spectroscopy signals of proteins dissolved in water. 相似文献
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The problem of multiuser detection in wireless communications systems adopts,in flat-fading channels, a blind source separation (BSS) formulation ofinstantaneous linear mixtures. This contribution addresses the closed-formsolutions to BSS in the complex-mixture scenario. The algebraic devices whichspan a unifying framework for the complex BSS closed-form estimators aredeveloped. With the aid of these tools, results originally encountered in thereal-mixture case are extended to the complex case, thus highlighting theremarkable parallelism existing between the real and complex problems in thecontext of their analytic solutions. Computer simulations illustrate thetheoretical results and compare the proposed methods to other BSS procedures. 相似文献
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Blind Decomposition of Transmission Light Microscopic Hyperspectral Cube Using Sparse Representation
《IEEE transactions on medical imaging》2009,28(8):1317-1324
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为了降低语音信号盲源分离算法的延时,提高其准确性和稳定性,本文结合传统盲源分离技术和深度神经网络的优势,提出了一种基于ICA独立分量分析和复数神经网络的二麦阵列盲源分离技术。本文将复数递归神经网络和独立分量分析方法有机融合,提出一种基于时频域的双通道复数神经网络,同时解决了独立分量分析中的排列问题。所提方法利输入混合信号利用复数域神经网络计算初始化分离矩阵,神经网络输出采用复数域形式,利用复数学习标签估计复数矩阵,然后采用独立分量分析方法获得目标分离矩阵。实验数据表明,所提方法相较于其它独立分量分析方法提高了盲源分离的实时性和准确性。 相似文献
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Based on the floating-point representation and taking advantage of scaling factor indetermination in blind source separation (BSS) processing, we propose a scaling technique applied to the separation matrix, to avoid the saturation or the weakness in the recovered source signals. This technique performs an automatic gain control in an on-line BSS environment. We demonstrate the effectiveness of this technique by using the implementation of a division-free BSS algorithm with two inputs, two outputs. The proposed technique is computationally cheaper and efficient for a hardware implementation compared to the Euclidean normalisation. 相似文献
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针对现有盲源分离方法大多存在收敛速度慢、分离精度低的问题,提出一种基于改进人工蜂群(Artificial Bee Colony,ABC)算法的盲信号分离方法.在ABC的邻域搜索公式中自适应调整步长,并加入全局最优解指导项,增强局部趋化性搜索能力.改进的ABC算法保持了ABC全局搜索和局部搜索之间的平衡,使ABC算法可以达到更好的寻优效果,从而提高盲源分离算法的分离精度和稳定性.实验结果表明,提出的改进盲源分离算法可以有效地分离线性瞬时混合信号.与其它算法相比,该算法具有更优异的分离性能,并具有更快的收敛速度. 相似文献