Search results for " Classification"
showing 10 items of 1043 documents
Using Chemical Structural Indicators for Periodic Classification of Local Anaesthetics
2011
Algorithms for classification and taxonomy based on criteria as information entropy and its production are proposed. Some local anaesthetics, currently in use, are classified using five characteristic chemical properties of different portions of their molecules. Many classification algorithms are based on information entropy. When applying the procedures to sets of moderate size, an excessive number of results appear compatible with data and the number suffers a combinatorial explosion. However, after the equipartition conjecture one has a selection criterion between different variants resulting from classification between hierarchical trees. Information entropy and principal component anal…
Optimal band selection for future satellite sensor dedicated to soil science
2009
Hyperspectral imaging systems could be used for identifying the different soil types from the satellites. However, detecting the reflectance of the soils in all the wavelengths involves the use of a large number of sensors with high accuracy and also creates a problem in transmitting the data to earth stations for processing. The current sensors can reach a bandwidth of 20 nm and hence, the reflectance obtained using the sensors are the integration of reflectance obtained in each of the wavelength present in the spectral band. Moreover, not all spectral bands contribute equally to classification and hence, identifying the bands necessary to have a good classification is necessary to reduce …
Effects of morphometric descriptor changes on statistical classification and morphospaces
2004
Ten morphometric descriptors (five pairs of form and shape parameters) are used to describe the complex morphology of the first lower molar of two morphologically similar species, Microtus arvalis and M. agrestis. These descriptors are derived either from linear measurements or from outline analysis. The effects of these different descriptors on classical analysis as used in biology or palaeobiology are explored. First, the reliability of results in statistical classification is assessed. All of the descriptors discriminate well between the two species. The initial morphometric scheme (linear or outline) does not induce marked differences in statistical classification and the major discrepa…
Parasite infracommunities as predictors of harvest location of bogue (Boops boops L.): a pilot study using statistical classifiers
2005
The accuracy of classifying bogue (Boops boops) according to the fishery from which it was harvested was evaluated by applying several statistical classification techniques to fish parasite abundances. Bogue captured in 2001 in two fisheries off the Atlantic coast of Spain were compared with one off the Spanish Mediterranean coast. One hundred bogue were classified to each harvest location (fishery) using different numbers of parasite species chosen as predictors by a best subset method. Two parametric methods of classification (linear and quadratic discriminant analysis) were compared with two non-parametric approaches (k-nearest neighbour classification and feed-forward neural network) an…
Using mathematical morphology for unsupervised classification of functional data
2011
This paper is concerned with the unsupervised classification of functional data by using mathematical morphology. Different morphological operators are used to extract relevant structures of the functions (considered as sets through their subgraph representations). These operators can be considered as preprocessing tools whose outputs are also functional data. We explore some dissimilarity measures and clustering methods for the classification of the transformed data. Our approach is illustrated through a detailed analysis of two data sets. These techniques, which have mainly been used in image processing, provide a flexible and robust toolbox for improving the results in unsupervised funct…
Mean square rate of convergence for random walk approximation of forward-backward SDEs
2020
AbstractLet (Y,Z) denote the solution to a forward-backward stochastic differential equation (FBSDE). If one constructs a random walk$B^n$from the underlying Brownian motionBby Skorokhod embedding, one can show$L_2$-convergence of the corresponding solutions$(Y^n,Z^n)$to$(Y, Z).$We estimate the rate of convergence based on smoothness properties, especially for a terminal condition function in$C^{2,\alpha}$. The proof relies on an approximative representation of$Z^n$and uses the concept of discretized Malliavin calculus. Moreover, we use growth and smoothness properties of the partial differential equation associated to the FBSDE, as well as of the finite difference equations associated to t…
Assessment of the probabilities for evolutionary structural changes in protein folds.
2007
Abstract Motivation: The evolution of protein sequences can be described by a stepwise process, where each step involves changes of a few amino acids. In a similar manner, the evolution of protein folds can be at least partially described by an analogous process, where each step involves comparatively simple changes affecting few secondary structure elements. A number of such evolution steps, justified by biologically confirmed examples, have previously been proposed by other researchers. However, unlike the situation with sequences, as far as we know there have been no attempts to estimate the comparative probabilities for different kinds of such structural changes. Results: We have tried …
A PHASE TRANSITION FOR LARGE VALUES OF BIFURCATING AUTOREGRESSIVE MODELS
2019
We describe the asymptotic behavior of the number $$Z_n[a_n,\infty )$$ of individuals with a large value in a stable bifurcating autoregressive process, where $$a_n\rightarrow \infty $$ . The study of the associated first moment is equivalent to the annealed large deviation problem of an autoregressive process in a random environment. The trajectorial behavior of $$Z_n[a_n,\infty )$$ is obtained by the study of the ancestral paths corresponding to the large deviation event together with the environment of the process. This study of large deviations of autoregressive processes in random environment is of independent interest and achieved first. The estimates for bifurcating autoregressive pr…
MODERATE DEVIATION PRINCIPLES FOR BIFURCATING MARKOV CHAINS: CASE OF FUNCTIONS DEPENDENT OF ONE VARIABLE
2021
The main purpose of this article is to establish moderate deviation principles for additive functionals of bifurcating Markov chains. Bifurcating Markov chains are a class of processes which are indexed by a regular binary tree. They can be seen as the models which represent the evolution of a trait along a population where each individual has two offsprings. Unlike the previous results of Bitseki, Djellout \& Guillin (2014), we consider here the case of functions which depend only on one variable. So, mainly inspired by the recent works of Bitseki \& Delmas (2020) about the central limit theorem for general additive functionals of bifurcating Markov chains, we give here a moderate deviatio…
Classification of flavonoid compounds by using entropy of information theory
2013
A total of 74 flavonoid compounds are classified into a periodic table by using an algorithm based on the entropy of information theory. Seven features in hierarchical order are used to classify structurally the flavonoids. From these features, the first three mark the group or column, while the last four are used to indicate the row or period in a table of periodic classification. Those flavonoids in the same group and period are suggested to show maximum similarity in properties. Furthermore, those with only the same group will present moderate similarity. In this report, the flavonoid compounds in the table, whose experimental data in bioactivity and antioxidant properties have been prev…