Title
General Purpose Representation And Association Machine: Part 4: Improve Learning For Three-States And Multi-Tasks
Keywords
Error Control Coding; General Purpose Systems; Intelligent Machine
Abstract
In this paper, we continue our journey on how to use simple LDPC codes to build a GPRAM prototype. We examine a switch function in the system which will allow us to perform revision in code structures in the GPRAM prototype in future. In this study we focus on how to improve learning for three-state systems; how to learn using perfect codewords; and finally how to perform progressive learning methods to perform multi-tasks. We start to see that many interesting features begin to merge and some of them may have bioimplications which need to be explored further. © 2013 IEEE.
Publication Date
9-4-2013
Publication Title
Conference Proceedings - IEEE SOUTHEASTCON
Number of Pages
-
Document Type
Article; Proceedings Paper
Personal Identifier
scopus
DOI Link
https://doi.org/10.1109/SECON.2013.6567485
Copyright Status
Unknown
Socpus ID
84883221584 (Scopus)
Source API URL
https://api.elsevier.com/content/abstract/scopus_id/84883221584
STARS Citation
Li, Huihui and Wei, Lei, "General Purpose Representation And Association Machine: Part 4: Improve Learning For Three-States And Multi-Tasks" (2013). Scopus Export 2010-2014. 6213.
https://stars.library.ucf.edu/scopus2010/6213