Fuzzy Neural Network Automaton

In newly forty years, Fuzzy Signal Processing that is developed rapidly is technology field. Its application is very extensive for all kinds of aspect. The extracted technology and application of Fuzzy neural network automaton is an important component of Fuzzy Signal Processing technology. The main aim is made use of association of fuzzy neural network and automata by successive Processing and crisply using network. Some Value parameter (i.e. useful fuzzy knowledge) of ambiguous or distorted signal that have received is effectively extracted so that it is effective for pattern recognition. With the worse environment of modern electronic war signal, the information that is collected by radio from enemy's radiator or some value information that had destroyed is extracted for lots of parameters (i.e. lots of parameter combination estimation), these work have become more and more important and difficult. Especially, the deterministic finite-state automaton (DFA)(i.e. deterministic device) will not be effective for processing the thing when the signal is continuously various or ambiguous in various states. Thus, in this paper, some researches are done for recognition of fuzzy information after theories and applications of fuzzy neural network automaton are discussed. At the same time, some corresponding extracted methods of fuzzy finite-state automaton (FFA) and fuzzy infinite-state automaton (FIA) is introduced, and the convergence of FIA is discussed and the equivalence of various automata are also discussed. Some new methods of value theories and applications are presented. The corresponding simulated result in computer proved the availability of these methods. In this paper, main content are discussed as follows: 1. According to recognizing type of fuzzy signal (language), partition of all kinds of fuzzy automata corresponding to fuzzy languages are introduced Based on recognizing type of fuzzy signal, fuzzy languages families are classified. A hierarchy of fuzzy automata corresponding to the hierarchy of fuzzy languages families is introduced and their corresponding relation are discussed.