Sergey V. Ulyanov

Sergey V. Ulyanov, Ichiro Kurawaki, Viktor S. Ulyanov et al.

Strategy of intelligent cognitive control systems based on quantum and soft computing presented. Quantum self-organization knowledge base synergetic effect extracted from intelligent fuzzy controllers imperfect knowledge bases described. That technology improved of robustness of intelligent cognitive control systems in hazard control situations described with the cognitive neuro-interface and different types of robot cooperation. Examples demonstrated the introduction of quantum fuzzy inference gate design as prepared programmable algorithmic solution for board embedded control systems. The possibility of neuro-interface application based on cognitive helmet with quantum fuzzy controller for driving of the vehicle is shown.

Sergey V. Ulyanov, Fabio Ghisi, Ichiro Kurawaki et al.

There are important algorithms built upon a mixture of basic techniques described; for example, the Fast Fourier Transform (FFT) employs both Divide-and-Conquer and Transform-and-Conquer techniques. In this article, the evolution of a quantum algorithm (QA) is examined from an information theory viewpoint. The complex vector entering the quantum algorithmic gate - QAG is considered as an information source both from the classical and the quantum level. The analysis of the classical and quantum information flow in Deutsch-Jozsa, Shor and Grover algorithms is used. It is shown that QAG, based on superposition of states, quantum entanglement and interference, when acting on the input vector, stores information into the system state, minimizing the gap between classical Shannon entropy and quantum von Neumann entropy. Minimizing of the gap between Shannon and von Neumann entropies is considered as a termination criterion of QA computational intelligence measure.

Sergey V. Ulyanov, Viktor S. Ulyanov, Takakhide Hagiwara

A generalized strategy for the design of intelligent robust control systems based on quantum / soft computing technologies is described. The reliability of hybrid intelligent controllers increase by providing the ability to self-organize of imperfect knowledge bases. The main attention is paid to increasing the level of robustness of intelligent control systems in unpredictable control situations with the demonstration by illustrative examples. A SW & HW platform and support tools for a supercomputer accelerator for modeling quantum algorithms on a classical computer are described.