| Title |
Research of multidimensional data visualization using feed-forward neural networks |
| Translation of Title |
Tiesioginio sklidimo neuroninių tinklų taikymo daugiamačiams duomenims vizualizuoti tyrimai. |
| Authors |
Medvedev, Viktor |
| Full Text |
|
| Pages |
24 |
| Keywords [eng] |
neural networks ; multidimensional data visualization ; Sammon's mapping ; SAMANN |
| Abstract [eng] |
The research area of this work is the analysis of multidimensional data and the ways of improving apprehension of the data. Data apprehension is rather a complicated problem especially if the data refer to a complex object or phenomenon described by many parameters. The research object of the dissertation is artificial neural networks for multidimensional data projection. General topics that are related with this object: multidimensional data visualization; dimensionality reduction algorithms; errors of projecting data; the projection of the new data; strategies for retraining the neural network that visualizes multidimensional data; optimization of control parameters of the neural network for multidimensional data projection; parallel computing. The key aim of the work is to develop and improve methods how to efficiently minimize visualization errors of multidimensional data by using artificial neural networks. The results of the research are applied in solving some problems in practice. Human physiological data that describe the human functional state have been investigated. |
| Type |
Summaries of doctoral thesis |
| Language |
English |
| Publication date |
2008 |
