Designing of the Artificial Neural Network Model Trained by Using the Different Learning Algorithms to Classify the Electrocardiographic Signals

An artificial neural network model trained by using various learning algorithms is designed to classify the electrocardiographic signals in this study. The of constructed on structure consisting a multilayered perceptron based feed forward back propagation. A data pool built dataset consists 66 data’s taken from MIT BIH arrhythmia database perform training and testing processes model. process performed with 46 then accuracy tested via 20 data. 3 different achieve robust performance used for evaluated according percentage error. It illustrates that Levenberg–Marquardt algorithm obtains better classification result than other algorithms. proposed can be successfully signals.