This paper is basically a review paper on Perceptron Model in Machine Learning and Intelligent Systems. This paper expands on the formative years of neural networks, going back to the pioneering work of McCulloch and Pitts in 1943. It also focuses on the perceptron convergence theorem. This theorem proves convergence of the perceptron as a linearly separable pattern classifier in finite number time-steps. We have also covered the basic area of machine learning, different learning techniques and application of perceptron in different problem solving.
Prof. Dr. Bilal BİLGİN