A rule based machine learning approach to the nonlinear multifingered robot gripper problem
A scaling result for explosive processes.
A scratch removal method
We present a new type of scratch removal algorithm based on a causal adaptive multidimensional prediction. The predictor use available information from the failed pixel surrounding due to spectral and spatial correlation of multispectral data but not any information from failed pixel itself. Predictor parameters cannot be directly identified so a special approximation is introduced.
A selection property of the boolean -calculus and some of its applications
A selection-based formal description of an environment
A semantic construction of two-ary integers
To binary trees, two-ary integers are what usual integers are to natural numbers, seen as unary trees. We can represent two-ary integers as binary trees too, yet with leaves labelled by binary words and with a structural restriction. In a sense, they are simpler than the binary trees, they relativize. Hence, contrary to the extensions known from Arithmetic and Algebra, this integer extension does not make the starting objects more complex. We use a semantic construction to get this extension. This...
A Semantic-Oriented Architecture of a Functional Module for Personalized and Adaptive Access to the Knowledge in a Multimedia Digital Library
This article presents the principal results of the doctoral thesis “Semantic-oriented Architecture and Models for Personalized and Adaptive Access to the Knowledge in Multimedia Digital Library” by Desislava Ivanova Paneva-Marinova (Institute of Mathematics and Informatics), successfully defended before the Specialised Academic Council for Informatics and Mathematical Modelling on 27 October, 2008.This paper presents dissertation work on semantic-oriented architectures and models for personalized...
A semigroup characterization of dot-depth one languages
A Semi-Topological Classification of the Line Figures
A sharpening of the Parikh mapping
In this paper we introduce a sharpening of the Parikh mapping and investigate its basic properties. The new mapping is based on square matrices of a certain form. The classical Parikh vector appears in such a matrix as the second diagonal. However, the matrix product gives more information about a word than the Parikh vector. We characterize the matrix products and establish also an interesting interconnection between mirror images of words and inverses of matrices.
A sharpening of the Parikh mapping
In this paper we introduce a sharpening of the Parikh mapping and investigate its basic properties. The new mapping is based on square matrices of a certain form. The classical Parikh vector appears in such a matrix as the second diagonal. However, the matrix product gives more information about a word than the Parikh vector. We characterize the matrix products and establish also an interesting interconnection between mirror images of words and inverses of .
A short note on Perez’s approximation by dependence structure simplification
Perez’s approximations of probability distributions by dependence structure simplification were introduced in 1970s, much earlier than graphical Markov models. In this paper we will recall these Perez’s models, formalize the notion of a compatible system of elementary simplifications and show the necessary and sufficient conditions a system must fulfill to be compatible. For this we will utilize the apparatus of compositional models.
A simple algorithm for constructing Szemerédi's regularity partition.
A simple algorithm for the calculation of the characteristic polynomial and the eigenvalues of a hexagonal tape. (Ein einfacher Algorithmus zur Berechnung des charakteristischen Polynoms und der Eigenvectoren eines hexagonalen Bandes.)
A Simple and Relatively Efficient Triangulation of the n-Cube.
A simple bioclogging model that accounts for spatial spreading of bacteria.
A simple detailed proof for Goedel's incompleteness theorem
A simple proof of Valiant's lemma
A simple upper bound to the Bayes error probability for feature selection
In this paper, feature selection in multiclass cases for classification of remote-sensing images is addressed. A criterion based on a simple upper bound to the error probability of the Bayes classifier for the minimum error is proposed. This criterion has the advantage of selecting features having a link with the error probability with a low computational load. Experiments have been carried out in order to compare the performances provided by the proposed criterion with the ones of some of the widely...
A simplex trained neural network-based architecture for sensor fusion and tracking of target maneuvers
One of the major applications for which neural network-based methods are being successfully employed is in the design of intelligent integrated processing architectures that efficiently implement sensor fusion operations. In this paper we shall present a novel scheme for developing fused decisions for surveillance and tracking in typical multi-sensor environments characterized by the disparity in the data streams arriving from various sensors. This scheme employs an integration of a multilayer neural...