Quantum Inspired Intelligent Systems [electronic resource] / edited by Nadia Nedjah, Leandro dos Santos Coelho, Luiza de Macedo Mourelle.

Gaussian Quantum-Behaved Particle Swarm Optimization Applied to Fuzzy PID Controller Design -- Quantum-inspired genetic algorithms for flow shop scheduling -- Quantum Simulataneous Recurrent Networks for Content Addressable Memory -- Quantum Intelligent Mobile System -- Quantum Associative Pattern Retrieval -- Quantum-Inspired Evolutionary Algorithm for Numerical Optimization -- Calibration of the VGSSD Option Pricing Model using a Quantum-inspired Evolutionary Algorithm.

Research on applying principles of quantum computing to improve the engineering of intelligent systems has been launched since late 1990s. This emergent research field concentrates on studying on quantum computing that is characterized by certain principles of quantum mechanics such as standing waves, interference, quantum bits, coherence, superposition of states, and concept of interference, combined with computational intelligence or soft computing approaches, such as artificial neural networks, fuzzy systems, evolutionary computing, swarm intelligence and hybrid soft computing methods. This volume offers a wide spectrum of research work developed using soft computing combined with quantum computing systems.