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A maximum likelihood blind source separation algorithm is developed. The temporal dependencies are explained by assuming that each source is an autoregressive (AR) process and the distribution of the associated i.i.d. innovations process is described by generalized Gaussian distribution (GGD), which can fit a broader range of statistical distributions by varying the value of the steepness parameter...
Complexity pursuit is a recently developed algorithm using the gradient descent for separating interesting components from time series. It is an extension of projection pursuit to time series data and the method is closely related to blind separation of time-dependent source signals and independent component analysis. The goal is to find projections of time series that have interesting structure,...
This paper makes an approach to the floating ring seal device of the large rotary furnace of chemic industry in existing, the existing structure is improved to be a new combined seal device consisting of discharge-helix and floating ring and radial labyrinth. The seal effect is ameliorated, the abrasion value of seals is reduced and its life is prolonged. Thereby the product grade is heightened, energy...
This paper is about disposal of at the work surface of carbon steel casting supporting roller in the large rotator. Analyzing solderability of supporting roller. Discussing usual problem in the weld process and producing detail process method of solder. Through practical validation, the method is available, which has referential function for solder analogous with steel casting of the large rotator.
Independent component analysis (ICA) is a fundamental and important task in unsupervised learning, that was studied mainly in the domain of Hebbian learning. In this paper, we consider the estimation of the data model of ICA when Gaussian noise is present and the independent components are time dependent. The temporal dependencies are explained by assuming that each source is an autoregressive (AR)...
Non-invasive fetal electrocardiogram (FECG) extraction is a vital issue in biomedical signal processing and analysis. A promising approach is blind source extraction and many algorithms have been proposed in recent years. In this paper, we consider the blind extraction when Gaussian noise is present and the source signals combine the non-Gaussianity and the autocorrelations. According to the useful...
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