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On representation for nonGaussian ARMA processes 关于非澳大利亚ARMA过程的表示
Pub Date : 1997-07-21 DOI: 10.1109/HOST.1997.613551
K. Chandrasekhar, S. Joshi
A generalised predictor space representation (of nonlinearity order two and memory M) for nonGaussian and nonminimum phase ARMA processes is proposed here, by expanding the underlying Hilbert space of finite L/sub 2/ norm random variables, which is now composed of linear combinations of linear as well as second order nonlinear terms of the process samples. Here the higher order statistical information enters into the picture in a natural way through the nonlinear terms. It is expected that the geometrical structure provided by the proposed predictor space would simplify the modeling of these processes. A set of new innovation vectors is defined on this space. Some of the properties of the new space are presented. The finite dimensionality of the proposed predictor space, when the underlying process admits a nonGaussian and nonminimum phase ARMA representation is proved. The application of the proposed theory to estimate nonGaussian and nonminimum phase ARMA process parameters is also discussed.
本文通过扩展有限L/sub 2/范数随机变量的Hilbert空间,提出了非高斯和非最小相位ARMA过程的广义预测空间表示(非线性2阶和内存M),该空间现在由过程样本的线性和二阶非线性项的线性组合组成。在这里,高阶统计信息通过非线性项以一种自然的方式进入图像。预计所提出的预测空间所提供的几何结构将简化这些过程的建模。在这个空间上定义了一组新的创新向量。给出了新空间的一些性质。当底层过程允许非高斯和非最小相位ARMA表示时,所提出的预测空间具有有限维性。本文还讨论了该理论在估计非高斯相位和非最小相位ARMA过程参数中的应用。
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引用次数: 0
Linear algebraic approaches for (almost) periodic moving average system identification (几乎)周期移动平均系统辨识的线性代数方法
Pub Date : 1997-07-21 DOI: 10.1109/HOST.1997.613498
Ying-Chang Liang, A. R. Leyman, Xianda Zhang
This paper addresses the problem of (almost) periodic moving average (APMA) system identification. Two normal equations are established by using time varying higher order cumulants of the measurements, from which two new linear algebraic algorithms are presented for parameter estimation. Simulation examples are given to demonstrate the performance of these new approaches.
本文研究(几乎)周期移动平均(APMA)系统的辨识问题。利用测量值的时变高阶累积量建立了两个正态方程,并在此基础上提出了两种新的参数估计线性代数算法。仿真实例验证了这些新方法的性能。
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引用次数: 1
Zero-order statistics: a signal processing framework for very impulsive processes 零阶统计量:一个用于非常脉冲过程的信号处理框架
Pub Date : 1997-07-21 DOI: 10.1109/HOST.1997.613526
J.G. Gonzalez, D. W. Griffith, G. Arce
Techniques based on conventional higher-order statistics fail when the underlying processes become impulsive. Although methods based on fractional lower-order statistics (FLOS) have proven successful in dealing with heavy-tailed processes, they fail in general when the noise distribution has very heavy algebraic tails, i.e., when the algebraic tail constant is close to zero. In this paper we introduce a signal processing framework that we call zero-order statistics (ZOS). ZOS are well defined for any process with algebraic or lighter tails, including the full class of /spl alpha/-stable distributions. We introduce zero-order scale and location statistics and study several of their properties. The intimate link between ZOS and FLOS is presented. We also show that ZOS are the optimal framework when the underlying processes are very impulsive. All figures, simulations and source code utilized in this paper are reproducible and freely accessible in the Internet at http://www.ee.udel./edu//sup /spl sim//gonzalez/PUBS/HOS97a.
当底层过程变得冲动时,基于传统高阶统计的技术就失效了。尽管基于分数阶低阶统计量(FLOS)的方法已被证明在处理重尾过程方面是成功的,但当噪声分布具有非常重的代数尾时,即当代数尾常数接近于零时,它们通常会失败。本文介绍了一种称为零阶统计量(ZOS)的信号处理框架。对于任何具有代数尾或较轻尾的过程,包括完整类的/spl α /-稳定分布,都可以很好地定义ZOS。引入了零阶尺度和位置统计量,并研究了它们的一些性质。提出了ZOS与FLOS之间的密切联系。我们还表明,当底层过程非常冲动时,ZOS是最优框架。本文中使用的所有图形、模拟和源代码都可以在互联网上免费复制和访问http://www.ee.udel./edu//sup /spl sim//gonzalez/PUBS/HOS97a。
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引用次数: 33
On the modeling of network traffic and fast simulation of rare events using /spl alpha/-stable self-similar processes 基于/spl alpha/-稳定自相似过程的网络流量建模与罕见事件快速仿真
Pub Date : 1997-07-21 DOI: 10.1109/HOST.1997.613529
A. Karasaridis, D. Hatzinakos
We present a new model for aggregated network traffic based on /spl alpha/-stable self-similar processes which captures the burstiness and the long range dependence of the data. We show how the fractional Gaussian noise assumption fails and why our proposed model fits well by comparing real and synthesized network traffic. In addition, we show that we can speed up the simulation times for estimation of rare event probabilities, such as cell losses in ATM switches, by up to three orders of magnitude using /spl alpha/-stable modeling and importance sampling.
本文提出了一种基于/spl α -稳定自相似过程的网络流量聚合模型,该模型捕捉了数据的突发性和长期依赖性。通过比较真实和合成的网络流量,我们展示了分数高斯噪声假设是如何失败的,以及为什么我们提出的模型很适合。此外,我们表明,我们可以使用/spl alpha/-stable建模和重要性采样将罕见事件概率(如ATM交换机中的单元损失)的估计模拟时间加快三个数量级。
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引用次数: 12
Dimensionality reduction in higher-order-only ICA 纯高阶ICA的降维
Pub Date : 1997-07-21 DOI: 10.1109/HOST.1997.613538
L. De Lathauwer, B. De Moor, J. Vandewalle
Most algebraic methods for independent component analysis (ICA) consist of a second-order and a higher-order stage. The former can be considered as a classical principal component analysis (PCA), with a three-fold goal: (a) reduction of the parameter set of unknowns to the manifold of orthogonal matrices, (b) standardization of the unknown source signals to mutually uncorrelated unit-variance signals, and (c) determination of the number of sources. In the higher-order stage the remaining unknown orthogonal factor is determined by imposing statistical independence on the source estimates. Like all correlation-based techniques, this set-up has the disadvantage that it is affected by additive Gaussian noise. However it is possible to solve the problem, in a way that is conceptually blind to additive Gaussian noise, by resorting only to higher-order cumulants. The purpose of this paper is to explain how the dimensionality of the ICA-model can algebraically be reduced to the true number of sources in higher-order-only schemes.
大多数独立分量分析(ICA)的代数方法由二阶和高阶阶段组成。前者可以被认为是经典的主成分分析(PCA),具有三个目标:(a)将未知参数集约简为正交矩阵的流形,(b)将未知源信号标准化为相互不相关的单位方差信号,(c)确定源的数量。在高阶阶段,通过对源估计施加统计独立性来确定剩余的未知正交因子。像所有基于相关的技术一样,这种设置的缺点是它受到加性高斯噪声的影响。然而,有可能解决这个问题,以一种概念上对加性高斯噪声视而不见的方式,只求助于高阶累积量。本文的目的是解释如何用代数方法将ica模型的维数简化为纯高阶格式中的真实源数。
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引用次数: 17
Classification of linear modulations by a combination of different orders cyclic cumulants 不同阶循环累积量组合的线性调制分类
Pub Date : 1997-07-21 DOI: 10.1109/HOST.1997.613485
C. Martret, Pierre Marchand, J. Lacoume
The search for discriminating features is a crucial point when a modulation classification task is aimed. This paper introduces new features based on a combination of fourth- and second-order temporal cyclic cumulants. Such a combination enhances the theoretical discrimination that can be achieved by a single stationary cumulant, and moreover, the cyclic parameters become discriminating whereas it is not the case when they are considered at pure orders. As an application, we propose a process to classify 4-PSK vs. 16-QAM modulations. The classification is achieved by estimating the feature for the received signal, and comparing it with theoretical ones by a matched filter technique. Simulations show that though the cyclic parameters are a priori more discriminating than their stationary counterparts, the variance of their estimates may overcome this advantage.
在调制分类任务中,识别特征的搜索是一个关键问题。本文引入了基于四阶和二阶时间循环累积量组合的新特征。这样的组合增强了单个平稳累积量可以实现的理论判别,而且,循环参数变得具有判别性,而在纯阶下考虑时则不是这样。作为一种应用,我们提出了一个分类4-PSK与16-QAM调制的过程。分类是通过估计接收信号的特征,并通过匹配滤波技术将其与理论信号进行比较来实现的。模拟表明,虽然循环参数比平稳参数先验地更具判别性,但其估计的方差可能会克服这一优势。
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引用次数: 52
Separation of sinusoidal sources 分离正弦源
Pub Date : 1997-07-21 DOI: 10.1109/HOST.1997.613544
C. Servière, V. Capdevielle, J. Lacoume
A particular source separation problem is addressed in this paper. We mainly focus on the separation of convolutive mixtures of rotating machine noises when the rotation speeds are close. Three specific points are developed. In the first point, we study the feasibility of the separation of periodic signals, regarding the hypothesis of random and non gaussian sources. We also discuss about the hypothesis of independence between the sources, as a function of the rotation speeds. In the second point, we analyze the performances of the source separation for close rotation speeds. They are linked to a partial correlation between the machine noises. Then, we propose a new method for very close rotation speeds, which takes into account this partial dependence between the sources.
本文讨论了一个特殊的源分离问题。本文主要研究转速较近时旋转机械噪声卷积混合的分离问题。具体有三点。在第一点中,我们研究了在随机和非高斯源假设下周期信号分离的可行性。我们还讨论了源之间独立的假设,作为旋转速度的函数。第二点分析了近转速下的源分离性能。它们与机器噪音之间的部分相关性有关。然后,我们提出了一种非常接近转速的新方法,该方法考虑了源之间的部分依赖。
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引用次数: 2
Nonlinearly constrained optimisation using a penalty-transformation method for Volterra parameter estimation 基于惩罚变换法的Volterra参数估计非线性约束优化
Pub Date : 1997-07-21 DOI: 10.1109/HOST.1997.613502
T. Stathaki
This paper forms a part of a series of studies we have undertaken, where the problem of nonlinear signal modelling is examined. We assume that the observed "output" signal is derived from a Volterra filter that is driven by a Gaussian input. Both the filter parameters and the input signal are unknown and therefore the problem can be classified as blind or unsupervised in nature. In the statistical approach to the solution of the above problem we seek for equations that relate the unknown parameters of the Volterra model with the statistical parameters of the "output" signal to be modelled. These equations are highly nonlinear and their solution is achieved through a novel constrained optimisation formulation. The results of the entire modelling scheme are compared with other contributions.
本文构成了我们所进行的一系列研究的一部分,其中对非线性信号建模问题进行了研究。我们假设观察到的“输出”信号来自一个由高斯输入驱动的Volterra滤波器。滤波器参数和输入信号都是未知的,因此该问题在本质上可以归类为盲或无监督。在解决上述问题的统计方法中,我们寻求将Volterra模型的未知参数与要建模的“输出”信号的统计参数联系起来的方程。这些方程是高度非线性的,它们的解是通过一种新的约束优化公式实现的。将整个模拟方案的结果与其他贡献进行了比较。
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引用次数: 2
Blind system identification in an impulsive environment 脉冲环境下系统的盲辨识
Pub Date : 1997-07-21 DOI: 10.1109/HOST.1997.613521
Jijun Yin, A. Petropulu
A method is presented for blind system identification in an impulsive environment, where the system output is described by a symmetric /spl alpha/-stable (S/spl alpha/S) law. The method employs either the phase or the magnitude of the recently proposed /spl alpha/-spectrum of the system output. It is much simpler than the method proposed previously which also relies on the phase or magnitude of the /spl alpha/-spectrum, and provides the system cepstrum via closed form expressions.
提出了一种脉冲环境下系统输出由对称/spl α /-稳定(S/spl α /S)律描述的系统盲辨识方法。该方法采用最近提出的系统输出的/spl alpha/-频谱的相位或幅度。它比先前提出的依赖于/spl α /-谱的相位或幅值的方法简单得多,并通过封闭形式表达式提供系统倒谱。
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引用次数: 0
DOA estimation using blind separation of sources 基于盲分离源的DOA估计
Pub Date : 1997-07-21 DOI: 10.1109/HOST.1997.613537
M. Hirari, M. Hayakawa
We propose a new approach for the estimation of DOA for polarized EM waves using blind separation of sources. In this approach we use a vector-sensor, a sensor whose output is a complete set of the EM field components of the irradiating wave and we reconstruct the waveforms of all the original signals; that is, all the EM components of the source's field. The blind separation of sources is made iteratively using a recurrent Hopfield-like single layer neural network. The simulation results for two sources have been investigated. We have considered coherent and incoherent sources, and also the case of varying DOA's vis-a-vis to the sensor and a varying polarization.
提出了一种利用源盲分离估计极化电磁波DOA的新方法。在这种方法中,我们使用矢量传感器,其输出是辐射波的电磁场分量的完整集合,我们重建所有原始信号的波形;即源场的所有EM分量。采用递归类hopfield单层神经网络进行源的盲分离。对两种源的模拟结果进行了研究。我们考虑了相干源和非相干源,以及相对于传感器的不同DOA和不同偏振的情况。
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引用次数: 11
期刊
Proceedings of the IEEE Signal Processing Workshop on Higher-Order Statistics
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