New neural network based approach helps to discover hidden Russian parliament voting patterns

IEEE International Conference on Neural Networks - Conference Proceedings

Volumn , Issue , 2006, Pages 3486-3491

  Frolov, Alexander A ^a   Husek, Dusan ^b   Polyakov, Pavel ^c   Rezankova, Hana ^d  

^a INSTITUTE OF HIGHER NERVOUS ACTIVITY AND NEUROPHYSIOLOGY   (Russian Federation)

^b INSTITUTE OF MATHEMATICS   (Czech Republic)

^c RUSSIAN ACADEMY OF SCIENCES   (Russian Federation)

^d UNIVERSITY OF ECONOMICS   (Czech Republic)

Author keywords

[No Author keywords available]

Indexed keywords

BOOLEAN FUNCTIONS; COMPUTATIONAL EFFICIENCY; COMPUTER SIMULATION; HOPFIELD NEURAL NETWORKS; PROBLEM SOLVING;

BOOLEAN FACTOR ANALYSIS; SIMULATED DATA; VOTING PATTERNS;

PATTERN RECOGNITION;

EID: 40649125065     PISSN: 10987576     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ijcnn.2006.247354     Document Type: Conference Paper

References (19)