Nonlinear Independent Factor Analysis by Hierarchical Models
نویسندگان
چکیده
The building blocks introduced earlier by us in [1] are used for constructing a hierarchical nonlinear model for nonlinear factor analysis. We call the resulting method hierarchical nonlinear factor analysis (HNFA). The variational Bayesian learning algorithm used in this method has a linear computational complexity, and it is able to infer the structure of the model in addition to estimating the unknown parameters. We show how nonlinear mixtures can be separated by first estimating a nonlinear subspace using HNFA and then rotating the subspace using linear independent component analysis. Experimental results show that the cost function minimised during learning predicts well the quality of the estimated subspace.
منابع مشابه
Linear and Nonlinear Multivariate Classification of Iranian Bottled Mineral Waters According to Their Elemental Content Determined by ICP-OES
The combinations of inductively coupled plasma-optical emission spectrometry (ICP-OES) and three classification algorithms, i.e., partial least squares discriminant analysis (PLS-DA), least squares support vector machine (LS-SVM) and soft independent modeling of class analogies (SIMCA), for discriminating different brands of Iranian bottled mineral waters, were explored. ICP-OES was used for th...
متن کاملAnalysis and Investigation of Landslide Hazard Zoning using Hybrid Model of Hierarchical Analysis and Surface Density
Identification of susceptible areas to landslide occurrence is one of the basic measures for reduction of the possible risk and hazard management. The main goal of this research is to compare the applicability of two statistical landslide hazard zonation models, valuing area accumulation and Analytical Hierarchy Process (AHP),in Ziarat Watershed, Gorgan, Golestan Province.In a review of previou...
متن کاملLearning a Hierarchical Belief Network of Independent Factor Analyzers
Many belief networks have been proposed that are composed of binary units. However, for tasks such as object and speech recognition which produce real-valued data, binary network models are usually inadequate. Independent component analysis (ICA) learns a model from real data, but the descriptive power of this model is severly limited. We begin by describing the independent factor analysis (IFA...
متن کاملDetermination of the Best Hierarchical Clustering Method for Regional Analysis of Base Flow Index in Kerman Province Catchments
The lack of complete coverage of hydrological data forces hydrologists to use the homogenization methods in regional analysis. In this research, in order to choose the best Hierarchical clustering method for regional analysis, base flow and related index were extracted from daily stream flow data using two parameter recursive digital filters in 43 hydrometric stations of the Kerman province. Ph...
متن کاملTrajectory tracking of under-actuated nonlinear dynamic robots: Adaptive fuzzy hierarchical terminal sliding-mode control
In recent years, underactuated nonlinear dynamic systems trajectory tracking, such as space robots and manipulators with structural flexibility, has become a major field of interest due to the complexity and high computational load of these systems. Hierarchical sliding mode control has been investigated recently for these systems; however, the instability phenomena will possibly occur, especia...
متن کامل