Automatic ECG Analysis for Preliminary and Detailed Diagnostics Based on Scale-space Representation

A novel approach of automatic ECG analysis based on scale-scale signal representation is proposed. The approach uses curvature scale-space representation to locate main ECG waveform limits and peaks and may be used to correct results of other ECG analysis techniques or independently. Moreover dynamic matching of ECG CSS representations provides robust preliminary recognition of ECG abnormalities which has been proven by experimental results.

Bulgariana: A Bulgarian Aggregator to Europeana

Europeana is the European virtual museum which was established in 2008. Its ambition is to create a common space allowing to access the cultural heritage of Europe from a single portal, by creating a network in all European countries. To make the initiative technically possible, Europeana has built a technological infrastructure to aggregate metadata from the different Europeana countries and memory institutions, while keeping the original digitized content on their sites. This paper presents Bulgariana, the Bulgarian chapter of Europeana. It is part of the technical infrastructure of Europeana, an established technical aggregator of Bulgarian cultural heritage content. It uses the two Europeana representation models ESE and EDM. Bulgariana is also a community building initiative putting in place a Bulgarian wide network of professionals and institutions working together to preserve and present Bulgarian cultural heritage around the world.

A New Approach for Eliminating the Spurious States in Recurrent Neural Networks

As is well known, the Convergence Theorem for the Recurrent Neural Networks, is based in Lyapunov ́s second method, which states that associated to any one given net state, there always exist a real number, in other words an element of the one dimensional Euclidean Space R, in such a way that when the state of the net changes then its associated real number decreases. In this paper we will introduce the two dimensional Euclidean space R2, as the space associated to the net, and we will define a pair of real numbers ( x, y ) , associated to any one given state of the net. We will prove that when the net change its state, then the product x ⋅ y will decrease. All the states whose projection over the energy field are placed on the same hyperbolic surface, will be considered as points with the same energy level. On the other hand we will prove that if the states are classified attended to their distances to the zero vector, only one pattern in each one of the different classes may be at the same energy level. The retrieving procedure is analyzed trough the projection of the states on that plane. The geometrical properties of the synaptic matrix W may be used for classifying the n-dimensional state- vector space in n classes. A pattern to be recognized is seen as a point belonging to one of these classes, and depending on the class the pattern to be retrieved belongs, different weight parameters are used. The capacity of the net is improved and the spurious states are reduced. In order to clarify and corroborate the theoretical results, together with the formal theory, an application is presented.

A Characterization of Weakly Lindelöf Determined Banach Spaces

2000 Mathematics Subject Classification: 46B26, 46B03, 46B04.

Well-Posedness and Conditioning of Optimization Problems

AMS subject classification: 49K40, 90C31.

An Iterative Procedure for Solving Nonsmooth Generalized Equation

2000 Mathematics Subject Classification: 47H04, 65K10.