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Start Over Creator Mouček, Roman

1. Coherence of EEG Signals and Biometric Signals of Handwriting under Influence of Nicotine, Alcohol, and Light Drugs

Creator:
Maršálek, Tomáš, Matoušek, Václav, Mautner, Pavel, Merta, Michal, and Mouček, Roman
Format:
bez média and svazek
Type:
model:article and TEXT
Subject:
computerized EEG signal evaluation, biometric signals, and signal coherence
Language:
English
Description:
Subject matter of investigations being carried out at the University of West Bohemia in Pilsen and described in this chapter is the objective evaluation of possible coherence of EEG signals and signals of handwriting generated by special developed BiSP pen. The influence of nicotine, alcohol and light drugs on the vigility and activity of human operators was investigated and evaluated; the results of the experiments being realized during the last five months are summarized in the last paragraph.
Rights:
http://creativecommons.org/publicdomain/mark/1.0/ and policy:public

2. Processing and categorization of Czech written documents using neural networks

Creator:
Mautner, Pavel and Mouček, Roman
Format:
bez média and svazek
Type:
model:article and TEXT
Subject:
Document categorization, WEBSOM, SOM, ART-2, neural networks, and document semantics
Language:
English
Description:
The Kohonen Self-organizing Feature Map (SOM) has been developed for clustering input vectors and for projection of continuous high-dimensional signal to discrete low-dimensional space. The application area, where the map can be also used, is the processing of text documents. Within the project WEBSOM, some methods based on SOM have been developed. These methods are suitable either for text documents information retrieval or for organization of large document collections. All methods have been tested on collections of English and Finnish written documents. This article deals with the application of WEBSOM methods to Czech written documents collections. The basic principles of WEBSOM methods, transformation of text information into the real components feature vector and results of documents classification are described. The Carpenter-Grossberg ART-2 neural network, usually used for adaptive vector clustering, was also tested as a document categorization tool. The results achieved by using this network are also presented.
Rights:
http://creativecommons.org/publicdomain/mark/1.0/ and policy:public