In this paper, we study the ability of learning automata-based schemes in escaping from local minima when standard backpropagation (BP) fails to 2nd the global minima. It is demonstrated through simulation that learning automata-based schemes compared to other schemes such as SAB, Super SAB, Fuzzy BP, adaptive steepness method, and variable learning rate method have a higher ability to escape f...

In this paper, traditional methods of edge detection and their problems are discussed. After that high performance method for edge detection that is fuzzy logic based image processing is used for accurate and noise free edge detection and Cellular Learning Automata (CLA) is used for enhance the previously-detected edges with the help of the repeatable and neighborhood-considering nature of CLA....

Algebraic properties and structures of intuitionistic $$L-$$ fuzzy multiset finite automata (ILFMA) are discussed through congruences on a semigroup in this paper. Firstly, we put forward the notion compatible relation, monoid associated with relation can be effectively constructed, construct two monoids different congruence relations given ILFMA, then prove that they isomorphic. Furthermore, u...

For a givenweighted finite automaton over a strong bimonoid we construct its reducedNerode automaton, which is crisp-deterministic and equivalent to the original weighted automaton with respect to the initial algebra semantics.We show that the reducedNerode automaton is even smaller than theNerode automaton, which was previously used in determinization related to this semantics. We determine ne...

This paper investigates the application of the computational model of Cellular Automata (CA) for pattern classification of real valued data. A special class of CA referred to as Fuzzy CA (FCA) is employed to design the pattern classifier. It is a natural extension of conventional CA, which operates on binary string employing boolean logic as next state function of a cell. By contrast, FCA emplo...