Handwritten Pattern Recognition of Digits and Special Characters using CMAC Neural Network

Pattern Recognition is a classifying process that is attributed to any number of input within a set of classes. Researches reveal that recognizing and classifying a complicated system is a difficult task; therefore, in this research it is benefit from CMAC neural method. A recommended system is a handmade text as input and to recognition its characters by using CMAC neural network. The character matrix consists of each character in text and the related character to the phase is adapted. Through studying different aspects of letters and characters, this is regarded as exact system for recognizing letter and numbers in handwriting text.

کلیدواژه ها:

Recognizing Sample ، Classification ، CMAC Neural Network ، Recognizing Phase