Ce papier présente un modèle génératif et son estimation permettant la visualisation de données binaires. Notre approche est basée sur un modèle de mélange de lois de Bernoulli par blocs et les cartes de Kohonen probabilistes. La méthode obtenue se montre à la fois parcimonieuse et pertinente en pratique.

Development of meaningful elearning materials has become critical for many organisations in the corporate space, particularly those whose workforce is spread over huge geographical areas. Perhaps even located in different countries, and/or different campuses. The Next GTM network is providing rural and regional customers with their first-ever taste of broadband connectivity. The Next GTM networ...

A topographic surface can be modeled as a graph, a visibility graph in terms of how each point location is visible to every other. This paper demonstrates various structural properties of visibility patterns with a topographic surface from a graph perspective, which could be important for landscape planning. This paper illustrates the fact that the visibility graph with a topographic surface is...

For land±atmosphere interaction studies several Topmodel based land-surface schemes have been proposed. For the implementation of such models over the continental (and global) scales, statistical properties of the topographic indices are derived using GTOPO30 (30-arc-second; 1 km resolution) DEM data for North America. River basins and drainage network extracted using this dataset are overlaid ...

One of the important properties of SOM is its topology preservation of the input data. The topographic error is one of the techniques proposed to measure how well the continuity of the map is preserved. However, this topographic error is only applicable to the crisp SOM algorithms and cannot be adapted to the fuzzy SOM (FSOM) since FSOM does not assign a unique winning neuron to the input patte...

Dimension-reducing feature extraction neural network techniques which also preserve neighbourhood relationships in data have traditionally been the exclusive domain of Kohonen self organising maps. Recently, we introduced a novel dimension-reducing feature extraction process, which is also topographic, based upon a Radial Basis Function architecture. It has been observed that the gener-alisatio...

The vision of Linked Topographic Data is critical for the Semantic Web, since topographic data are fundamental to a wide range of geoscientific analyses and mapping of geographic phenomena. Terrain datasets are probably the most important for Linked Topographic Data. Terrain is computationally represented using a continuous field data model (2-D surfaces), but the Semantic Web needs discrete ob...

A topographic map is a two-dimensional, nonlinear approximation of a potentially high-dimensional data manifold, which makes it an appealing instrument for visualizing and exploring high-dimensional data. The Self-Organizing Map (SOM) is the most widely used algorithm, and it has led to thousands of applications in very diverse areas. In this chapter, we will introduce the SOM algorithm, discus...

Numerosity, the set size of a group of items, is processed by the association cortex, but certain aspects mirror the properties of primary senses. Sensory cortices contain topographic maps reflecting the structure of sensory organs. Are the cortical representation and processing of numerosity organized topographically, even though no sensory organ has a numerical structure? Using high-field fun...

Recently, di+erent models of the statistical structure of natural images (and sequences) have been proposed. Maximizing sparseness, or alternatively temporal coherence of linear 1lter outputs leads to the emergence of simple cell properties. Taking account of the basic dependencies of linear 1lter outputs enables modelling of complex cell and topographic properties as well. Here, we propose a u...