ARTIFICIAL NEURAL NETWORKS: INTRODUCTION AND USE OF PERCEPTRON ALGORITHM IN BIOSSYSTEMS - BONINI NETO, Alfredo; BONINI, Carolina dos Santos Batista (Revista Brasileira de Engenharia de Biossistemas, 2010)
Artificial Neural Networks are computational model inspired by way living organisms manipulate the information received, and with that, presents learning capability, adaptability and generalization of knowledge. Moreover, the operation of an Artificial Neural Network is based on parallelism, resembling as the brain deals with information received by the neurons. The present work describes the study of artificial neural network Perceptron as a linear classifier to distinguish two types of fruits (orange (citrus sinensis Osbeck) and tangerine ’Ponkan’ (citrus reticulate Blanco)) using two basic processes performed by an artificial neural network, the phases of training or learning and operation phase. The main objective is to show the functioning of these phases.