𝔖 Bobbio Scriptorium
✦   LIBER   ✦

Learning automata based classifier

✍ Scribed by Seyed-Hamid Zahiri

Publisher
Elsevier Science
Year
2008
Tongue
English
Weight
247 KB
Volume
29
Category
Article
ISSN
0167-8655

No coin nor oath required. For personal study only.

πŸ“œ SIMILAR VOLUMES

Learning automata based dynamic guard ch
Learning automata based dynamic guard channel algorithms
✍ Hamid Beigy; M.R. Meybodi πŸ“‚ Article πŸ“… 2011 πŸ› Elsevier Science 🌐 English βš– 556 KB

In this paper, we first propose two learning automata based decentralized dynamic guard channel algorithms for cellular mobile networks. These algorithms use learning automata to adjust the number of guard channels to be assigned to cells of network. Then, we introduce a new model for nonstationary

On the classifiability of cellular autom
On the classifiability of cellular automata
✍ John T. Baldwin; Saharon Shelah πŸ“‚ Article πŸ“… 2000 πŸ› Elsevier Science 🌐 English βš– 106 KB

Based on computer simulations Wolfram presented in several papers conjectured classiΓΏcations of cellular automata into four types. We show a natural formalization of his rate of growth suggestion does not provide a classiΓΏcation (even probabilistically) of all cellular automata: For any rational p;

Asynchronous cellular learning automata
Asynchronous cellular learning automata
✍ Hamid Beigy; M.R. Meybodi πŸ“‚ Article πŸ“… 2008 πŸ› Elsevier Science 🌐 English βš– 641 KB

Cellular learning automata is a combination of cellular automata and learning automata. The synchronous version of cellular learning automata in which all learning automata in different cells are activated synchronously, has found many applications. In some applications a type of cellular learning a

A new classifier based on information th
A new classifier based on information theoretic learning with unlabeled data
✍ Kyu-Hwa Jeong; Jian-Wu Xu; Deniz Erdogmus; Jose C. Principe πŸ“‚ Article πŸ“… 2005 πŸ› Elsevier Science 🌐 English βš– 348 KB

Supervised learning is conventionally performed with pairwise input-output labeled data. After the training procedure, the adaptive system's weights are fixed while the testing procedure with unlabeled data is performed. Recently, in an attempt to improve classification performance unlabeled data ha