Jaringan Saraf Tiruan Pengenalan Pola Huruf Sistem Matriks dengan Algoritma Hebb Rule
DOI:
https://doi.org/10.30865/jurikom.v9i5.5015Keywords:
Artificial Intelligence, Artificial Neural Networks, Hebb, Bipolar Sigmoid, Pattern recognitionAbstract
The science of artificial intelligence is currently very developed, this can be seen from the development of patterns and characters of artificial intelligence. This stems from the need to maintain security and information related to data so that it can be adjusted with a confidentiality key in the form of pattern and character lock recognition. Pattern recognition consists of various kinds such as facial recognition patterns and fingerprint patterns. The problem in this study is the lack of understanding in maintaining data confidentiality so that the benefits of this research are able to maintain data confidentiality by using a matrix pattern. This study uses the Hebb rule method to obtain the final results. The matrix variable used is from x1 to x25 input and bias 1 with initial weight value 0, W and M patterns are initialized with character x worth 1 and character o worth -1 with bipolar output, U target 1 and S target -1, function f( net) is 1 if Y >= 0 and -1 if Y < 0. The final result after the search process is obtained the value W = -8 and M=-8which produces the same output as the target and can be recognized
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