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In this paper, we develop a novel classification algorithm that is based on the integration between competitive learning and the computational power of quantum computing. The proposed algorithm classifies an input into one of two binary classes even if the input pattern is incomplete. We use the entanglement measure after applying unitary operators to conduct the competition between neurons in order to find the winning class based on wining-take-all. The novelty of the proposed algorithm is shown in its application to the quantum computer. Our idea is validated via classifying the state of Reactor Coolant Pump of a Risky Nuclear Power Plant and compared with other quantum-based competitive neural networks model.

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With the extensive growth of the Internet, wireless technology, and multimedia applications, Quality of Service (QoS) monitoring and measurement of the networks have become important. Network measurements are carried out to obtain information about important QoS parameters such as delay, loss and jitter. Each type of multimedia applications has its own requirements and limits on these parameters. To evaluate the QoS of multimedia applications transmitted over wireless networks, a fuzzy logic assessment system has been developed. The system showed how the end-to-end QoS could be measured without the necess ity for complex mathematical models. The measured QoS we re classified into three categories Good, Average, and Poor regions. In addition, and based on the proposed system, the distributions and the overall QoS were estimated. The results indicated that the measured QoS was a good indication of the network conditions and resource availability.

Mobile ad-hoc and vehicular networks are excellent examples of the proliferation of wireless data communication technologies. A mobile ad-hoc networks (MANET) consists of wireless devices which can dynamically be setup and can operate without any centralized control. One promising application of MANETs is the vehicular ad-hoc networks (VANETs). A VANET is a combination of an architectural network and an ad-hoc network. VANETs are distributed self-organizing networks of mobile vehicles. This chapter introduces both MANETs and VANETs, their characteristics and challenges, and presents the various protocols and applications optimized for them.