D-2-1 Quantum Neural Network's Theory and Its Calculation(General Session in English (2))

Abstract

We rewrote the famous Bayes' theory into quantum Bayes' Form. In order to practice that process, all of classical probabilities were necessary that they were reinterpreted into operators, state vectors, probability amplitude, and expectation values. The difference between classical version and quantum form was whether interference's term exists or not. Quantum Bayes' form had the additional term Re(Int). At junctions, all of pure states were mixed. Some attenuated states were generated instead of all pure states at junction. In neurons, examples of those areas meant neuro-synaptic junctions, ephapse of axons, and endplate of muscles, and so on. Final state vector ∖B> had the various information of environmental state at the conditions of the mixed and reduced purities. So, if we would like to obtain the pure state and the other quantities, we needed take a series of mathematical operations as making expectation values