Search results for "multidimensional"
showing 10 items of 181 documents
Adaptive Importance Sampling: The past, the present, and the future
2017
A fundamental problem in signal processing is the estimation of unknown parameters or functions from noisy observations. Important examples include localization of objects in wireless sensor networks [1] and the Internet of Things [2]; multiple source reconstruction from electroencephalograms [3]; estimation of power spectral density for speech enhancement [4]; or inference in genomic signal processing [5]. Within the Bayesian signal processing framework, these problems are addressed by constructing posterior probability distributions of the unknowns. The posteriors combine optimally all of the information about the unknowns in the observations with the information that is present in their …
A new Adaptive and Progressive Image Transmission Approach using Function Superpositions
2010
International audience; We present a novel approach to adaptive and progressive image transmission, based on the decomposition of an image into compositions and superpositions of monovariate functions. The monovariate functions are iteratively constructed and transmitted, one after the other, to progressively reconstruct the original image: the progressive transmission is performed directly in the 1D space of the monovariate functions and independently of any statistical properties of the image. Each monovariate function contains only a fraction of the pixels of the image. Each new transmitted monovariate function adds data to the previously transmitted monovariate functions. After each tra…
Local dimensionality reduction and supervised learning within natural clusters for biomedical data analysis
2006
Inductive learning systems were successfully applied in a number of medical domains. Nevertheless, the effective use of these systems often requires data preprocessing before applying a learning algorithm. This is especially important for multidimensional heterogeneous data presented by a large number of features of different types. Dimensionality reduction (DR) is one commonly applied approach. The goal of this paper is to study the impact of natural clustering--clustering according to expert domain knowledge--on DR for supervised learning (SL) in the area of antibiotic resistance. We compare several data-mining strategies that apply DR by means of feature extraction or feature selection w…
Space-Time FPCA Clustering of Multidimensional Curves.
2018
In this paper we focus on finding clusters of multidimensional curves with spatio-temporal structure, applying a variant of a k-means algorithm based on the principal component rotation of data. The main advantage of this approach is to combine the clustering functional analysis of the multidimensional data, with smoothing methods based on generalized additive models, that cope with both the spatial and the temporal variability, and with functional principal components that takes into account the dependency between the curves.
Selmer's Multiplicative Algorithm
2011
Abstract.The behavior of the multiplicative acceleration of Selmer's algorithm is widely unknown and no general result on convergence has been detected yet. Solely for its 2-dimensional, periodic expansions, there exist some results on convergence and approximation due to Fritz Schweiger. In this paper we show that periodic expansions of any dimension do in fact converge and that the coordinates of the limit points are rational functions of the largest eigenvalue of the periodicity matrix.
Fractional wavelet transform
1997
The wavelet transform, which has had a growing importance in signal and image processing, has been generalized by association with both the wavelet transform and the fractional Fourier transform. Possible implementations of the new transformation are in image compression, image transmission, transient signal processing, etc. Computer simulations demonstrate the abilities of the novel transform. Optical implementation of this transform is briefly discussed.
Dynamic programming for 2-D discrete linear systems
1989
The authors calculate the optimal control of 2-D discrete linear systems using a dynamic programming method. It is assumed that the system is described with Roesser's state-space equations for which a 2-D sequence of inputs minimizing the given performance criterion is calculated. The method is particularly suitable for problems with bounded states and controls, although it can also be applied for unbounded cases. One numerical example is given. >
On the metric properties of dynamic time warping
1987
Recently, some new and promising methods have been proposed to reduce the number of Dynamic Time Warping (DTW) computations in Isolated Word Recognition. For these methods to be properly applicable, the verification of the Triangle Inequality (TI) by the DTW-based Dissimilarity Measure utilized seems to be an important prerequisite.
The role of prognostic stratification on prescription of anticoagulants in older patients with atrial fibrillation : a multicenter, observational, pr…
2022
Background: Literature suggests that different risks of mortality could influence physicians in prescribing or not anticoagulants in older patients with atrial fibrillation (AF). The Multidimensional Prognostic Index (MPI) can be considered a tool for the detection of multidimensional frailty. The aim of this cross-sectional study was to evaluate whether prescription patterns of oral anticoagulants exist, based on MPI values. Methods: Older hospitalised patients (age >= 65 years) with non-valvular AF were included across 24 European centres. MPI was calculated using validated and standardised tools derived from a comprehensive geriatric assessment. Other functional and clinical information …
Multidimensional financial development, exporter behavior and export diversification
2020
Financial development shapes export sector performance because exporters need external finance and face credit constraints. Previous empirical research has relied largely on single-country studies. The Exporter Dynamics Database (EDD), which features firm-level exports from over 60 countries, reveals differences in the microstructure of the export sector across countries. In this paper, we first provide new evidence that these differences are related to cross-country variation in financial development and structure. Second, we combine the EDD and multidimensional data on financial development with a global database on export diversification. This study is the first to examine how macrolevel…