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Multilayer hierarchical models
 Béger, Michal ; Štanclová, Jana (advisor) ; Petříčková, Zuzana (referee)
This diploma thesis deals with hierarchical associative memories (HAM), which have been experimentally analysed only in the case of two layer hierarchy so far. The aim of this thesis is to study existing hierarchical models and evaluate experimentally their performance for more than two layer hierarchy. We show, that existing hierarchical model HAM is not suitable for three or more layer hierarchy. For that reason, we propose a new version of hierarchical model (called HAM-N), which enables utilization of any number of layers. The new model HAM-N uses the structure of the HAM model. However, due to modied learning and recall process, the HAM-N model eliminates the above-mentioned drawbacks of the HAM model. Finally, the HAM-N model is experimentally studied with respect to processing of large amounts of correlated patterns. Thesis also includes analysis of experiment results.
Detailed record
Multilayer hierarchical models
 Béger, Michal ; Petříčková, Zuzana (referee) ; Štanclová, Jana (advisor)
This diploma thesis deals with hierarchical associative memories (HAM), which have been experimentally analysed only in the case of two layer hierarchy so far. The aim of this thesis is to study existing hierarchical models and evaluate experimentally their performance for more than two layer hierarchy. We show, that existing hierarchical model HAM is not suitable for three or more layer hierarchy. For that reason, we propose a new version of hierarchical model (called HAM-N), which enables utilization of any number of layers. The new model HAM-N uses the structure of the HAM model. However, due to modied learning and recall process, the HAM-N model eliminates the above-mentioned drawbacks of the HAM model. Finally, the HAM-N model is experimentally studied with respect to processing of large amounts of correlated patterns. Thesis also includes analysis of experiment results.
Detailed record

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