Artificial Intelligence and Electrical & Electronics Engineering: AIEEE Open Access
Artificial Neural Networks with Extensions and Correlated Run
Abstract
Mirzakhmet Syzdykov
In this work we are demonstrating the supervised power of artificial neural networks within the scope of performance and other loyal theoretical background, which lays in-between the theory and practice, still we don’t have a definite answer if it was defined before, since the applicated role of artificial intelligence which come to the trend during the recent time, thus, in this short work we are addressing the theoretical conveniences observed since the first humanity statement on the account of the human and artificial consciousness and mimics between them which lays the ground- breaking technological revolution to its first step. We give also the definition of the relation of probabilistic models towards construction of finite automata recognizing certain patterns for the given probability set and we are giving the definition of filter which is a rational relation between the repeated sequences in non-deterministic finite automata, we also show that it can be used in constructing deterministic automataon with respect to the filter condition, the definition of the aggregator normalization form of data in a database is also given. In this work we give the new algorithm for proving facts in logical directed graph using dynamic programming approach.