Perceptron

The perceptron is one of the historical starting points of artificial neural networks and can be viewed as a single-layer linear decision mechanism. It multiplies inputs by weights, sums them, and produces an output through a thresholding process. It provides an instructive foundation for linearly separable problems, but its inability to model nonlinear patterns makes clear why deeper network architectures became necessary.