Five-Layered Neural Fuzzy Closed-Loop Hybrid Control System with Compound Bayesian Decision-Making Process for Classification Cum Identification of Mixed Connective Conjunct Consonants and Numerals

Abstract

The OCR generation systems are most sophisticated active field and interesting conversional discovery for digitalization of handwritten and typed imprecise data into machine detectable characters. The fuzzy logic system processes the data with help of primary-based bunch set of knowledge. Fuzzy logic closed-loop system having very good successful rate of frame work for decision-based functions, can derive the fuzzy rules to build the decision-making procedure and detect the letters human to system to human. Artificial neural networks are compatible and the best area to solve the pattern cum text recognition tasks. The innovative combinational based characteristic of neural fuzzy-based closed-loop hybrid system proposing a five-layered approach with technical ideas, solutions solve the critical problems in the field of character, face, symbol recognition procedure, and estimating the density ratio. Recognition of single text, numbers is easy than the recognition of mixed connective conjunct consonants. Because of their variations, various handwritten pen-stroke pulses, tuning the initial and end position of each conjunct consonant, some consonants are connected and mixed with their left-cum right-side placed conjuncts, numerals, and symbols. Many languages such as Arabic, Hindi, Urdu, Telugu, and Tamil represent syllabic, symbol scripted form, and most of words formed with the mixed conjuncts, mixed cum touched consonants, mixed conjuncts with numerals in their representation. This research approach has proposed the five-layered neural fuzzy closed-loop hybrid system with compound Bayesian decision-making process holding good outcome for classification cum identification of mixed connective conjunct consonants with their numerals. The recognition process can start with categorizing total text into two forms; normal conjunct consonants and mixed connective conjunct consonants. The permutation futures of five-layered neural fuzzy closed-loop hybrid system represent inputs as neurons, convert it into fuzzy set inputs, and then apply the fuzzification process with desirable fuzzy knowledge based rules to produce the required output through responses. The compound Bayesian decision-making process is used to perform the operations of probability of sum to unity to reduce the recognition problems in the mixed connective conjunct consonants.