共查询到19条相似文献，搜索用时 328 毫秒
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独立分量分析是近年发展起来的一种高效的信号分离方法,主要对观测的混合信号进行分离或提取各个源信号。简要介绍了ICA的概念、基本原理以及FastICA算法,通过实际语音信号的仿真,证明了用FastICA算法分离语音信号可以取得较好的结果。 相似文献
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小波变换在信号去噪的应用中有很大的优势,它弥补了傅里叶变换在信号去噪中的局限。小波变换在时间域和频率域都具有良好的局部特性,可以聚焦到信号的任意细节。根据信号的特性利用小波变换的处理方法能够有效的将有用信号与噪声分离开来从而达到去噪的效果。 相似文献
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对已有的基于MP(匹配追踪)算法去除地震资料中的随机噪声的方法进行了一定改进。通过对地震信号特性的研究及传统Ricker子波的分析,对传统Ricker子波进行了改进,并将其作为MP分解中构造原子库的基函数。改进后的Ricker子波能更加匹配的表示地震信号,去除地震随机噪声中,基于改进后的Ricker子波进行MP去随机噪声较基于Gabor原子的方法具有更好的去噪效果。 相似文献
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近些年,信号处理在理论与方法方面发展速度很快。独立分量分析技术(Independent Component Analysis,简称ICA)是信号处理领域近十几年才发展起来的一种新的理论和方法,并且逐步的成熟化与系统化,变成了信号处理领域内重要的组成部分。本文主要讨论线性瞬时混合情况下语音信号盲分离算法,阐述了算法原理,进行了实验仿真,以此来证明算法的有效性。 相似文献
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本文将计算智能(CI)现代信号处理方法有机地结合起来进行损伤检测,提供了一种机械传动系统故障诊断方法。采用离散小波分解和小波包变换,分别对去噪后的信号进行分解,对齿轮不同状态下的信号进行了研究。重构了小波变换后的各层信号,并计算了各层信号的能量,得到了信号的能量分布特征。分别利用小波分析与神经网络相结合和小波包变换与支持向量机相结合的计算智能算法对获得的齿轮特征信号进行了分析、识别和比较。研究表明,该方法可以很好的用于设备损伤检测领域。 相似文献
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比较了ICA方法进行面部表情识别的两种架构ICA1和ICA2。采用欧式、城区、余弦KNN和6种核函数的SVM算法进行识别,比较了不同的距离函数和核函数对整体识别率和单个表情识别率的影响。实验表明:ICA1整体上优于ICA2;对于KNN算法,在ICA1下KNN+城区距最优,t检验不显著,在ICA2下,KNN+余弦距最优,t检验显著;SVM算法对ICA1有效,对ICA2失效;在ICA1下,对SVM算法,线性、径向基和Sigmoid核取得相同的识别率;惊奇是最好识别的表情,高兴是最难识别的表情。最后利用神经科学对视觉脑区的最新研究,得出稀疏的特征比稀疏的编码能够取得更好的表情识别率。 相似文献
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《Journal of The Franklin Institute》2006,343(4-5):340-351
Data compression techniques are commonly used to achieve a low bit rate in the digital representation of signals for efficient processing, transmission, and storage. In this paper, a new technique for lossless compression of seismic data is introduced. The technique consists of two stages. The first stage is a modified linear prediction with discrete coefficients that is developed based on the assumption that the seismic data can be modeled as a sum of finite number of complex sinusoids in additive noise. In the second stage, the parameters and residual sequence of seismic data model are bi-level coded. Experimental results performed using real seismic data are presented to demonstrate the effectiveness of the new modeling approach. 相似文献
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Enrique A. González-Velasco Emilio Sanvicente 《Journal of The Franklin Institute》1980,310(2):135-142
The analytic representation of band-pass signals, which is extremely useful in information transmission and radar, is usually obtained by first introducing the Hilbert transform of a signal. We consider this procedure artificial, and propose here to follow the opposite path, which leads, in a natural way, to a motivated definition of the Hilbert transform. The key to this procedure is to show how, as a simple application of the Fourier integral, every band-pass signal can be expressed as the real part of a low frequency signal which modulates an exponential. Such a representation, called the analytic signal, is then used to define the Hilbert transform in a natural manner. Finally, we show that the term analytic signal is motivated by the fact that this signal is the restriction to the real axis of a function defined and analytic (holomorphic) in the upper half of the complex plane. 相似文献
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对时间序列的预测是一项重要的数据挖掘技术。本文将独立分量分析方法和小波神经网络相结合,建立一种ICA—WNN预测模型,并应用于风力发电功率时间序列预测。仿真结果表明所建模型具有较好的泛化性能,得到了较高的预测精度。 相似文献
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Hot strip mill process (HSMP) plays a pivotal role in steel manufacturing industry, but involves significant complexity. Several faults could cause the decreasing evaluation of the key performance indicators (KPIs). Partial least squares (PLS) model has been popularly accepted for KPI-monitoring tasks, whereas some drawbacks have been reported such as high false alarm rate and strict limitation of Gaussian distribution. In this paper, a new scheme is designed without any distributional priority. The process information is extracted by the independent component analysis (ICA) and principal component analysis (PCA) one after another to obtain the Non-Gaussianity and Gaussianity rooted in process variables. Then the correlation canonical analysis (CCA), a classic tool of analyzing the correlation of two data sets, will be utilized to incorporate the process information and KPIs. Finally, two KPI-related indices are formed respectively, which are both bounded by key density estimation based approach. In the end, application of the new approach in a real steel plant will be demonstrated, where the comparison with PLS based results is covered. 相似文献
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杨立强 《中国科学院研究生院学报》2005,22(3):359-363
利用LOG算子和改进相干算法相结合来提高信噪比和地震资料分辨率 ,并同其他方法作了比较 .模型数据与实际数据的应用效果证明 ,该方法具有较强的信噪分离作用 ,能有效提高地震资料分辨率 ,该方法是实用的 . 相似文献
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微弱信号检测技术的研究 总被引：1，自引：0，他引：1
微弱信号检测就是利用近代电子学和信号处理方法从噪声中提取有用信号,其关键在于抑制噪声,恢复、增加和提取有用信号.本文将从信号处理系统信噪比的改善来简单地论述微弱信号检测的原理,重点介绍了用相关检测法和取样积分法检测微弱信号的原理、方法和应用. 相似文献
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Lynsey Dubbeld 《Ethics and Information Technology》2003,5(3):151-162
At the most mundane level, CCTV observes bodies, and as such attaches great importance to the specific features of the human
body. At the same time, however, bodies tend to disappear, as they are represented electronically by the camera monitors and,
in the case of image recording, by the computer systems processing data. The roles of bodies(either as targets of surveillance
or as translations into flows of disembodied information), however, are not unimportant or inconsequential, but may in fact
give rise to a number of tangible ethical dilemmas. Firstly, the virtual representation of the embodied actor is not a neutral,
unproblematic process. Body representation techniques such as CCTV produce constructions of the subject that involve judgmental,
discriminatory processes of categorisation and are based on asymmetrical relations between observers and observed. Secondly,
the `data doubles' are not inconsequential: the representations of the body produced by CCTV can have palpable consequences
for the embodied self and its life chances. The widespread use of CCTV could therefore give rise to individual as well as
social issues, and possibly in a different manner than previous surveillance technologies. This fact signals the need for(re-)conceptualisations
of moral values (such as privacy) applicable to the case of CCTV which take into account the importance of bodily protections.
This revised version was published online in July 2006 with corrections to the Cover Date. 相似文献
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Wojciech Ros?oniec 《Journal of The Franklin Institute》2010,347(8):1452-1467
Radar systems usually had used digital signal processors for signal processing in the past. Such an approach has changed after introduction of a new type of general purpose PowerPC processor with very fast vector units called AltiVec. This new type of processor could realize various tasks performed earlier by several specialized processors. For instance it could be used for digital signal processing, tracking, fusion of data or communication with other functional blocks of radar. Its versatility and speed proved to be a superior solution in modern radar systems. It could also be programmed using C language instead of an assembler, what facilitated software development. Unfortunately the memory subsystem of computers built using this type of processor appeared to be too slow, and consequently slowed down the calculations. Therefore, the signal-processing software written for PowerPC processors with AltiVec vector units had to be accordingly optimized. The paper presents various optimization techniques and their effect on mean processing time of signal-processing software.The computer system built of industrial computers connected by the internal Ethernet is also presented in the paper. Individual computers of this system contain the multi-core PowerPC processors equipped with AltiVec vector units. The experimental model of the system is used for real-time digital processing of the multi-stream radar signals. The presented results of theoretical and experimental investigations show that the system is an effective, universal and cheaper computational platform than the corresponding, traditional multiprocessor platforms using the signal processors. Selected example recipes of writing the optimum and reliable application software are also given. 相似文献