Please use this identifier to cite or link to this item:
https://www.um.edu.mt/library/oar/handle/123456789/17810| Title: | Digital hardware implementation of self-organising maps |
| Authors: | Cutajar, Michelle Gatt, Edward Micallef, Joseph Grech, Ivan Casha, Owen |
| Keywords: | Self-organizing maps Neural networks (Computer science) Microelectromechanical systems Pattern recognition systems |
| Issue Date: | 2010 |
| Publisher: | Institute of Electrical and Electronics Engineers Inc. |
| Citation: | Cutajar, M., Gatt, E., Micallef, J., Grech, I., & Casha, O. (2010). Digital hardware implementation of self-organising maps. 15th IEEE Mediterranean Electrotechnical Conference (MELECON 2010), Valletta. 1123-1128. |
| Abstract: | In this paper a digital hardware implementation of the Self-Organising Maps (SOMs) for the application of handwritten digit recognition is presented. Two methods were implemented: Euclidean and Manhattan method. The highest recognition rate for both methods was calculated through three testing techniques. The highest recognition rates obtained are 71.267% and 63.667% for the Euclidean and the Manhattan methods respectively. Both methods were implemented on the Xilinx Spartan-3 200K gates (XC3S200) to compare their speed performance and area consumed. |
| URI: | https://www.um.edu.mt/library/oar//handle/123456789/17810 |
| Appears in Collections: | Scholarly Works - FacICTMN |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| Digital hardware implementation of self-organising maps.pdf Restricted Access | Digital hardware implementation of Self-Organising Maps | 253.78 kB | Adobe PDF | View/Open Request a copy |
Items in OAR@UM are protected by copyright, with all rights reserved, unless otherwise indicated.