A Quantum Model for Autonomous Learning Automata

摘要: The idea of information encoding on quantum bearers and its quantum-mechanical processing has revolutionized our world brought mankind the verge enigmatic era technologies. Inspired by this idea, in present paper we search for advantages field machine learning. Exploiting only basic properties Hilbert space, superposition principle mechanics measurements, construct a analog Rosenblatt's perceptron, which is simplest learning machine. We demonstrate that perceptron superiors classical counterpart capabilities. In particular, show able to learn an arbitrary (Boolean) logical function, perform classification previously unseen classes even recognize superpositions learned -- task high importance applied medical engineering.