A continuous rosenblatt quantum perceptron

Quantum neural networks are expected to provide the theoretical framework to implement machine learning on quantum computers. We develop a continuous Rosenblatt quantum perceptron which represents the generalization of the McCulloch-Pitts quantum perceptron existing in the literature. We implement its quantum circuit on a IBM quantum computer.