1 citations · 1 across the 4 of their papers we have counts for
4 papers
The Combined Technique for Detection of Artifacts in Clinical Electroencephalograms of Sleeping Newborns
Vitaly Schetinin, Joachim Schult
In this paper we describe a new method combining the polynomial neural network and decision tree techniques in order to derive comprehensible classification rules from clinical ele…
A Neural-Network Technique to Learn Concepts from Electroencephalograms
Vitaly Schetinin, Joachim Schult
A new technique is presented developed to learn multi-class concepts from clinical electroencephalograms. A desired concept is represented as a neuronal computational model consist…
Neural-Network Techniques for Visual Mining Clinical Electroencephalograms
Vitaly Schetinin, Joachim Schult, Anatoly Brazhnikov
In this chapter we describe new neural-network techniques developed for visual mining clinical electroencephalograms (EEGs), the weak electrical potentials invoked by brain activit…
Learning Polynomial Networks for Classification of Clinical Electroencephalograms
Vitaly Schetinin, Joachim Schult
We describe a polynomial network technique developed for learning to classify clinical electroencephalograms (EEGs) presented by noisy features. Using an evolutionary strategy impl…