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Description: ICA算法The algorithm is equivalent to Infomax by Bell and Sejnowski 1995 [1] using a maximum likelihood formulation. No noise is assumed and the number of observations must equal the number of sources. The BFGS method [2] is used for optimization. The number of independent components are calculated using Bayes Information Criterion [3] (BIC), with PCA for dimension reduction.-ICA algorithm:The algorithm is equivalent to Infomax by Bell and Sejnowski 1995 [1] using a maximum likelihood formulation. No noise is assumed and the number of observations must equal the number of sources. The BFGS method [2] is used for optimization. The number of independent components are calculated using Bayes Information Criterion [3] (BIC), with PCA for dimension reduction.
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Author: 陈互 |
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Description: This a Bayesian ICA algorithm for the linear instantaneous mixing model with additive Gaussian noise [1]. The inference problem is solved by ML-II, i.e. the sources are found by integration over the source posterior and the noise covariance and mixing matrix are found by maximization of the marginal likelihood [1]. The sufficient statistics are estimated by either variational mean field theory with the linear response correction or by adaptive TAP mean field theory [2,3]. The mean field equations are solved by a belief propagation method [4] or sequential iteration. The computational complexity is N M^3, where N is the number of time samples and M the number of sources.
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Author: 陈互 |
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Description: 程序是对心电信号进行噪声去除，采用的是数度较快的滤波器组，能快速完成计算任务-procedures of the ECG signal for noise removal, using a few degrees faster filters can rapidly complete computing tasks
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Author: 唐娜 |
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Description: 提出了一种新的自适应盲源分离算法。在无噪音实时两源两传感器的情况下, 一旦观
测信号被白化, 只需要辨识一个特定的旋转矩阵就可以完成盲源分离, 并给出了能表征该旋转矩阵的角的自适应估计器。仿真结果表明, 当满足源峭度和不为零的条件时, 这种方法是一种稳定的和有效的分离算法。-proposes a new adaptive algorithm for blind source separation. In the absence of real-time two noise sources two sensor case, once observed signal was albino, only need to identify a specific rotation matrix can be completed blind source separation, given to the characterization of the angle of rotation matrix adaptive estimation. Simulation results show that when the source met in front of zero degrees and the conditions, this method is a stable and effective separation algorithm.
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Description: I developed an algorithm for using local ICA in denoising multidimensional data. It uses delay embedded version of the data, clustering and ICA for the separation between data and noise. -I developed an algorithm for using local ICA in denoising multidimensional data. It uses delay embedded version of the data, clustering and ICA for the separation between data and noise.
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Author: sunny |
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Description: 仿真函数
（1），函数形式为：
其中， 是零均值单位方差的高斯噪声。输入 服从[0，1] 均匀分布，且相互独立。样本长度为1000组，将其分为三组，自由选择200组作为模型训练数据，自由选择100组作为检验数据，其余的作为长期检验数据。
（2）
其中x1~x4相互独立， ， 为白噪声
-Simulation function (1), function of the form: which is the zero mean unit variance Gaussian noise. Enter the subject [0,1] uniformly distributed and independent of each other. Sample length of 1000 group, will be divided into three groups, to free choice of 200 group as a model training data, to free choice of 100 group as test data, and the rest as a long-term test data. (2) x1 ~ x4 which are independent of each other, for white noise
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Author: 扬之江 |
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Description: 采用滤波器组，将盲分离与声源定位结合在一起。滤波器组中分别进行子带处理，并且在每个子带中进行声源定位，最后综合所有子带估计的方向得到多个声源的方位信息，同时将声源信息作为ICA分析的约束条件，可以在色噪声及多得到更好的盲分离效果。其优势在于用滤波器组进行多次的估计声源方向，再加以合适的权值均衡后即可得到更优的估计。-The use of filters will be blind source separation and sound localization together. Filter group were sub-band treatment, and in each sub-band in Sound Source Localization, and finally all the sub-band is estimated to be more than the direction of sound source location information, as well as sound source information as ICA analysis of the binding conditions, colored noise can be better and many of the blind source separation effect. Its advantage lies in a number of filter banks with estimated sound source direction, coupled with an appropriate balance weights can be obtained after the better estimate.
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Author: chen |
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Description: ：由于许多传统的去噪方法在强背景噪声情况下提取声音信号的能力变弱甚至失效， 提出
应用独立成分分析( I C A) 方法对声音信号进行特征提取， 并证明了这种 I C A 变换能增强语音和音
乐信号的超高斯性． 在此基础上， 应用 I C A基函数作为滤波器， 通过阈值化的去噪方法对含有强高
斯背景噪声的声音信号进行去噪仿真实验． 结果表明， 本方法明显优于传统的均值滤波和小波去噪
方法， 为强背景噪声下弱信号的检测提供 了新的途径．-: As many of the traditional de-noising method in case of strong background noise, the ability to extract the voice signal even weaker failure, the application of independent component analysis (ICA) method of voice signal feature extraction, and prove that this transformation can be enhanced voice ICA and music of super-Gaussian signals. On this basis, the application of ICA basis function as a filter, through the threshold of the denoising method of Gaussian background noise contains strong voice signal denoising simulation. The results show that this method is obviously superior to the traditional mean filtering and wavelet denoising methods for the strong background noise under the weak signal detection provides a new way.
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Author: 金振东 |
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Description: 一种新的盲源分离方法
Injecting noise for analysing the stability of ICA components
-Injecting noise for analysing the stability of ICA components
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Author: bfield |
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Description: This a Bayesian ICA algorithm for the linear instantaneous mixing model with additive Gaussian noise.-This is a Bayesian ICA algorithm for the linear instantaneous mixing model with additive Gaussian noise.
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Author: Vladimir |
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Description: 独立成分分析算法降低原始数据噪声，并提取特征值，非常有用得数据去噪程序。-Independent component analysis algorithm reduces the raw data noise, and extract characteristic value, is more helpful data denoising procedure.
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Size: 52224 |
Author: 陶帅 |
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Description: 基于最大信噪比的ICA算法，在盲信号分离中用处比较大-ICA algorithm based on maximum signal to noise ratio, useful in blind signal separation in the larger
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Author: atops |
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Description: ICA算法可以将噪声信号分解为一系列独立的分量（ICs），这样就可以对各独立分量进行单独的研究和分析。首先叙述了柴油机噪声信号的特性。预测模型表明：发动机噪声信号满足ICA计算的要求。然后介绍了ICA模型的相关理论。举例说明ICA方法分离信号的有效性，以及ICA方法对小能量噪声的分离的有效性。连续小波变换来显示了各独立分量ICs在时频域内的特性。由采集信号分离得到噪声源信号可以作为发动机的理论预测和设计依据。-he ICA algorithm can be decomposed into a series of independent noise signal of the component (sysu), so that we can to each individual independent component analysis and research. First describes the characteristics of diesel engine noise signal. Forecasting model shows: the engine noise signal satisfy the requirements. ICA calculation Then introduces the related theoretical model of ICA. Illustrate the effectiveness of the method of ICA and separated signal to noise ICA method of separation of energy efficiency. Continuous wavelet transform to display the independent components in time-frequency domain sysu properties. By gathering signal noise signal can be obtained as the engine of the theoretical prediction and design basis.
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Author: 王霞 |
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Description: 独立分量分析（ICA）以非高斯源信号为研究对象，在统计独立的假设下，对多路观测到的混合信号进行盲信号分离，已广泛应用于无线通信、生物信号提取、语音信号处理、图像处理和噪声抑制等领域。 -The independent component analysis (ICA) addresses non-Gaussian source signals under amusing independent each other, it performs blind separation for multi-channel observed signals. It has widely applied in wireless communication, biological signals extraction, audio signal processing, image processing, and noise reducing and so on.
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Author: zhaojianli |
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Description: 针对精密孔锉肖帅口工过程中易出现颤振、导致精密孔表面质量下降，如何能快速、准确识别出颤振征兆发生问题，提出基于独立分量分析(ICA)的锉削振动信号信噪分离方法，以实现对镬削颤振征兆信号的快速分离。该方法据颤振信号的时频特点，利用经验模态分解(EMD)对铿削振动信号进行分解 对EMD分解所得各本征模态分量(IMF)构造出的虚拟通道进行ICA分析，分离出包含颤振发生征兆的信号。实验结果表明，利用EMD和ICA对镬削振动信号进行分解处理，可快速分离出撞削颤振征兆信号，为后续颤振识别预报及抑制环节提供基础，从而有效提高精密孔的表面加工质量。
-For precision hole Xiao Shuai port workers filing process prone to chatter, resulting in decreased precision bore surface quality, and how to quickly and accurately identify the signs occur flutter problem, based on independent component analysis (ICA) of the signal to noise vibration signal cutting and filing separation, in order to achieve rapid symptom pan cut flutter signal separation. The method according to the time-frequency dither signal characteristics, the use of empirical mode decomposition (EMD) for Keng cut vibration signal decomposition levy on the proceeds of EMD modal component of each of the (IMF) constructed ICA virtual channel analysis, separation a signal containing signs flutter occurs. Experimental results show that the use of EMD and ICA to wok cut vibration signal decomposition process can be quickly isolated signs of signal collision cut flutter, flutter provide the basis for subsequent identification forecast and suppression links, thus effectively improving
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Author: wangming |
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Description: ica的算法，独立成分分析，剔除噪声，数据处理-ica algorithm, independent component analysis, eliminate noise, data processing
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Size: 1024 |
Author: 孙会文 |
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Description: ICA快速算法，提高分类效果 滤波 源信号所含的高斯白噪声越多，分离后得到的信号与源信号相比误差越大，效果越差；所含高斯白噪声越少，分离效果越好-Fast ICA algorithm to improve the classification results more contained in the source signal filtering Gaussian white noise, the signal obtained with the source signal separation errors compared to the bigger, the worse contained fewer white Gaussian noise, the better separation
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Author: 潘蕴文 |
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Description: 包含收发两个客户端的链路级通信程序,欢迎大家下载学习，独立成分分析算法降低原始数据噪声，ICA（主分量分析）算法和程序，进行波形数据分析,包括回归分析和概率统计，FIR 底通和带通滤波器和IIR 底通和带通滤波器，包含了阵列信号处理的常见算法。- Contains two clients receive link-level communications program, Welcome to download the study, Independent component analysis algorithm reduces the raw data noise, ICA (Principal Component Analysis) algorithm and procedures, Waveform data analysis, Including regression analysis and probability and statistics, Bottom-pass and band-pass FIR and IIR filter bottom pass and band-pass filter, Contains a common array signal processing algorithm.
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Author: esbuadehv |
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Description: Contains two clients receive link-level communications program, Welcome to download the study, Independent component analysis algorithm reduces the raw data noise, ICA (Principal Component Analysis) algorithm and procedures, Waveform data analysis, Including regression analysis and probability and statistics, Bottom-pass and band-pass FIR and IIR filter bottom pass and band-pass filter, Contains a common array signal processing algorithm.
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Size: 5120 |
Author: deicbg
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Description: 在测量的数据中存在一定的噪声干扰， 需要将其进行的滤波处理，此程序即为快熟ICA的滤波程序(There is a certain noise interference in the measured data, so it needs to be filtered. This program is a fast mature ICA filter program)
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Author: 小小飞鹤
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