Search results for "Kernel"
showing 10 items of 357 documents
Computerized delimitation of odorant areas in gas-chromatography-olfactometry by kernel density estimation: Data processing on French white wines
2017
International audience; GC-O using the detection frequency method gives a list of odor events (OEs) where each OE is described by a linear retention index (LRI) and by the aromatic descriptor given by a human assessor. The aim of the experimenter is to gather OEs in a total olfactogram on which he tries to delimit odorant areas (OAs), then to compute each detection frequency. This paper proposes a computerized mathematical method based on kernel density estimation that makes up the total olfactogram as continuous and differentiable function from the OEs LRI only. The corresponding curve looks like a chromatogram, the peaks of which are potential OAs. The limits of an OA are the LRI of the t…
Enhancement and assessment of WKS variance parameter for intelligent 3D shape recognition and matching based on MPSO
2016
This paper presents an improved wave kernel signature (WKS) using the modified particle swarm optimization (MPSO)-based intelligent recognition and matching on 3D shapes. We select the first feature vector from WKS, which represents the 3D shape over the first energy scale. The choice of this vector is to reinforce robustness against non-rigid 3D shapes. Furthermore, an optimized WKS-based method for extracting key-points from objects is introduced. Due to its discriminative power, the associated optimized WKS values with each point remain extremely stable, which allows for efficient salient features extraction. To assert our method regarding its robustness against topological deformations,…
Statistics of transitions for Markov chains with periodic forcing
2013
The influence of a time-periodic forcing on stochastic processes can essentially be emphasized in the large time behaviour of their paths. The statistics of transition in a simple Markov chain model permits to quantify this influence. In particular the first Floquet multiplier of the associated generating function can be explicitly computed and related to the equilibrium probability measure of an associated process in higher dimension. An application to the stochastic resonance is presented.
Quantizations from reproducing kernel spaces
2012
Abstract The purpose of this work is to explore the existence and properties of reproducing kernel Hilbert subspaces of L 2 ( C , d 2 z / π ) based on subsets of complex Hermite polynomials. The resulting coherent states (CS) form a family depending on a nonnegative parameter s . We examine some interesting issues, mainly related to CS quantization, like the existence of the usual harmonic oscillator spectrum despite the absence of canonical commutation rules. The question of mathematical and physical equivalences between the s -dependent quantizations is also considered.
Inductive E.S.O. model evolution: towards a viable inference model of resilience dynamics.
2013
In this paper, we will present the last evolution of the Territorial Intelligence (TI) networking vulnerability model. To introduce it, we'll first describe a well-known late 80's model of socio-economic crack-up, known as "Silent Weapons for Quiet Wars", constituted by three passive components as potential energy, kinetic energy, and energy dissipation. To extend this model to social and ecological sustainability pillars, we propose to present the E(Economic)-S(Social)-O(Organic) IT-collaborative model, based on the three sustainability capitals. Goal of this model is the developement system viability computation, which related "Viability theory" computational framework is able to define s…
Observations of land use transformations during the Neolithic using exploratory spatial data analysis: contributions and limitations
2010
International audience; The settlement pattern analysis in archaeology implies some methodological questions. In this paper, we question some issues about the use of geostatistical methods for the observation of land use transformations during the Neolithic. We have developed two examples in Burgundy (France): the first one on a regional scale and the second one on a micro-regional scale. Using different ESDA approaches (Ripley’K function, Nearest Neighbour Distance, Kernel Density Estimation), we would like to underline what the methodological and archaeological contributions and their limits are. Both experiences point out that the results obtained depend not only on the analytical scale,…
Models and tools for territorial dynamic studies (chapter 1)
2012
As part of the ArchaeDyn project, a workgroup was formed to coordinate the development, implementation and application of methods and tools for spatial analysis. The workgroup's activities were directed at various problems. The first was to construct a grid common to all the workgroups and to homogenize the study areas used by the different workgroups in their databases. The 'confidence maps' method was suggested for assessing the quality and quantity of information inventoried in the databases. Confidence maps are produced from representation and reliability maps by simple map algebra and they can be considered as 'masks' for interpreting spatial analysis results. Finally, the research tea…
An Observation Framework for Multi-Agent Systems
2009
Existing middleware platforms for multi-agent systems (MAS) do not provide general support for observation. On the other hand, observation is considered to be an important mechanism needed for realizing effective and efficient coordination of agents. This paper describes a framework called Agent Observable Environment (AOE) for observation-based interaction in MAS. The framework provides 1) possibility to model MAS components with RDFbased observable soft-bodies, 2) support for both query and publish/subscribe style ontology-driven observation, and 3) ability to restrict the visibility of observable information using observation rules. Additionally, we report on an implementation of the fra…
Nonlinear data description with Principal Polynomial Analysis
2012
Principal Component Analysis (PCA) has been widely used for manifold description and dimensionality reduction. Performance of PCA is however hampered when data exhibits nonlinear feature relations. In this work, we propose a new framework for manifold learning based on the use of a sequence of Principal Polynomials that capture the eventually nonlinear nature of the data. The proposed Principal Polynomial Analysis (PPA) is shown to generalize PCA. Unlike recently proposed nonlinear methods (e.g. spectral/kernel methods and projection pursuit techniques, neural networks), PPA features are easily interpretable and the method leads to a fully invertible transform, which is a desirable property…
A principled approach to network-based classification and data representation
2013
Measures of similarity are fundamental in pattern recognition and data mining. Typically the Euclidean metric is used in this context, weighting all variables equally and therefore assuming equal relevance, which is very rare in real applications. In contrast, given an estimate of a conditional density function, the Fisher information calculated in primary data space implicitly measures the relevance of variables in a principled way by reference to auxiliary data such as class labels. This paper proposes a framework that uses a distance metric based on Fisher information to construct similarity networks that achieve a more informative and principled representation of data. The framework ena…