Ahmad Zarkasi, Aciek Ida Wuryandari, Multilayer processing architecture of RAM based neural network with memory optimization for navigation system
| Main Author: | Ahmad Zarkasi, zarkasi |
|---|---|
| Format: | Proceeding PeerReviewed application/pdf |
| Terbitan: |
, 2013
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| Subjects: | |
| Online Access: |
http://eprints.unsri.ac.id/4476/1/rict2013icevt2013_104.pdf http://ieeexplore.ieee.org/xpl/articleDetails.jsp?tp=&arnumber=6741494&queryText%3Dahmad+zarkasi http://eprints.unsri.ac.id/4476/ |
Daftar Isi:
- Robots also have been trusted to help human to complete difficult jobs, for example, finding for the earthquake, a fire, or a sinking ship victims. The robot must be reliable, clever and moving automatically. The aim of this study is to develop and apply the application of artificial RAM-based neural networks (WNNs) on a mobile robot using a multilayer processing architecture with memory optimizations on to address and input pattern, so that producing smart navigation model which it has a simpler computational load and faster execution time. The gained result from the first study was the percentage of memory optimization in the amount of 50%. This result obtained from the formerly RAM using 8 bit data width has been optimized to 4 bits. Both of the percentage of data optimization pattern is 93.75%. This percentage is obtained from the optimization pattern (pattern taken is 4 bits MSB), each 1 bit data can handle 15 unseen patterns.