Locally linear discriminate embedding for face recognition.
Locally weighted neural networks for an analysis of the biosensor response
This paper presents a semi-global mathematical model for an analysis of a signal of amperometric biosensors. Artificial neural networks were applied to an analysis of the biosensor response to multi-component mixtures. A large amount of the learning and test data was synthesized using computer simulation of the biosensor response. The biosensor signal was analyzed with respect to the concentration of each component of the mixture. The paradigm of locally weighted linear regression was used for retraining...
Logic and functional programming by retractions
Logic and functional programming by retractions : operational semantics
Logical Aggregation Based on Interpolative Boolean Algebra.
Logique combinatoire et linguistique : grammaire catégorielle combinatoire applicative
La Grammaire Catégorielle Combinatoire Applicative étend la Grammaire Catégorielle Combinatoire de Steedman par une association canonique entre les règles et des combinateurs de Curry d'une part et l'utilisation de métarègles qui contrôlent les opérations de changement de type d'autre part. Ce modèle est inclus dans le modèle général de la Grammaire Applicative et Cognitive (Desclés) avec trois niveaux de représentation : (i) le phénotype (expressions concaténées) ; (ii) le génotype (expressions...
M. M. Postnikov: his life, work and legacy
Majority multiplicative ordered weighting geometric operators and their use in the aggregation of multiplicative preference relations.
In this paper, we introduced the majority multiplicative ordered weighted geometric (MM-OWG) operator and its properties. This is a general type of the aggregate dependent weights which we have applied in geometric environment. The MM-OWG operator is based on the OWG operators and on the majority operators. We provide the MM-OWG operators to aggregate in a multiplicative environment, i.e. when it's necessary to aggregate information given on a ratio scale. Therefore, it allows us to incorporate...
Man and computer
Marginalization in models generated by compositional expressions
In the framework of models generated by compositional expressions, we solve two topical marginalization problems (namely, the single-marginal problem and the marginal-representation problem) that were solved only for the special class of the so-called “canonical expressions”. We also show that the two problems can be solved “from scratch” with preliminary symbolic computation.
Marginalization in multidimensional compositional models
Efficient computational algorithms are what made graphical Markov models so popular and successful. Similar algorithms can also be developed for computation with compositional models, which form an alternative to graphical Markov models. In this paper we present a theoretical basis as well as a scheme of an algorithm enabling computation of marginals for multidimensional distributions represented in the form of compositional models.
Marginalization like a projection.
This paper studies the problem of marginalizing convex polytopes of probabilities represented by a set of constraints. This marginalization is obtained as a special case of projection on a specific subspace. An algorithm that projects a convex polytope on any subspace has been built and the expression of the subspace, where the projection must be made for obtaining the marginalization, has been calculated.
Matematický popis přirozených jazyků
Mathématique et linguistique
MATHWARE – Special issue devoted to FLINS 2008 conference.
'Matrioshka's' soft approaches to personalized web exploration
Maximization of the information divergence from multinomial distributions
Max-min fuzzy neural networks for solving relational equations.
The Relational Equations approach is one of the most usual ones for describing (Fuzzy) Systems and in most cases, it is the final expression for other descriptions. This is why the identification of Relational Equations from a set of examples has received considerable atention in the specialized literature. This paper is devoted to this topic, more specifically to the topic of max-min neural networks for identification. Three methods of learning Fuzzy Systems are developed by combining the most...
Measuring criteria weights by means of Dimension Theory.
Measuring criteria weights in multicriteria decision making is a key issue in order to amalgamate information when reality is being described from several different points of view. In this paper we propose a method for evaluating those weights taking advantage of Dimension Theory, which allows the representation of the set of alternatives within a real space, provided that decision maker preferences satisfy certain consistency conditions. Such a representation allows a first information about possible...
Mechanical analogy of statement networks
The paper demonstrates briefly the reasoning capabilities in condition monitoring offered by systems based on statement networks. The usefulness of the networks considered results among others from possibilities of their optimization related to the minimization of contradictions between rules acquired from different knowledge sources. A mechanical analogy of such networks introduces an interpretation of statements as material points that are able to move. Dependencies between statements are considered...