Gray Level Image Edge Detection Using a Hybrid Model of Cellular Learning Automata and Stochastic Cellular Automata

OALib ◽  
2015 ◽  
Vol 02 (01) ◽  
pp. 1-8
Author(s):  
Nasim Vatani ◽  
Rasul Enayatifar
2004 ◽  
Vol 07 (03n04) ◽  
pp. 295-319 ◽  
Author(s):  
HAMID BEIGY ◽  
M. R. MEYBODI

The cellular learning automata, which is a combination of cellular automata, and learning automata, is a new recently introduced model. This model is superior to cellular automata because of its ability to learn and is also superior to a single learning automaton because it is a collection of learning automata which can interact with each other. The basic idea of cellular learning automata, which is a subclass of stochastic cellular learning automata, is to use the learning automata to adjust the state transition probability of stochastic cellular automata. In this paper, we first provide a mathematical framework for cellular learning automata and then study its convergence behavior. It is shown that for a class of rules, called commutative rules, the cellular learning automata converges to a stable and compatible configuration. The numerical results also confirm the theoretical investigations.


2015 ◽  
Vol 69 (9) ◽  
pp. 1282-1290 ◽  
Author(s):  
Mohammad Hasanzadeh Mofrad ◽  
Sana Sadeghi ◽  
Alireza Rezvanian ◽  
Mohammad Reza Meybodi

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