]. S. Haykin, . W. Haykin-]-t, B. Rondeau, D. Le, D. Maldonado et al., Learning and Adaptation in Cognitive Radios Using Neural Networks Cognitive radio formulation and implementation Cognitive Techniques: Physical and Link Layers in Cognitive Radio Technology Cognitive radio: an integrated agent architecture for software defined radio Learning ability in cognitive radio, Cognitive radio: brainempowered wireless communications Selected Areas in Communications 5th IEEE Consumer Communications and Networking Conference 1st International Conference on Cognitive Radio Oriented Wireless Networks and Communications Spectrum Management of Cognitive Radio Using Multi-agent Reinforcement Learning, Proceedings of the 9th International Conference on Autonomous Agents and Multiagent Systems (AAMAS) international conference on network application,protovols and services 2008. [Haykin, 1999] S. Haykin, Neural Networks: A Comprehensive Foundation.Upper Saddle River, pp.201-220, 1999.

]. J. Reed and . Reed, A new approach to signal classification using spectral correlation and neural networks Development of a Cognitive Engine and Analysis of WRAN Cognitive Radio Algorithms?Phase I, " Wireless @ Virginia Tech, Virginia Polytech Pattern based encoding for cognitive communication, Proc. 1st IEEE Int. Symp. New Frontiers DySPAN Proc. 3rd Int. Conf, pp.144-150, 2005.

]. O. Orcay and B. Ustundag, Pattern recognition in cognitive communication, 2008 23rd International Symposium on Computer and Information Sciences, pp.1-6, 2008.
DOI : 10.1109/ISCIS.2008.4717870

]. C. Blum and A. Roli, Metaheuristics in combinatorial optimization, ACM Computing Surveys, vol.35, issue.3, 2003.
DOI : 10.1145/937503.937505
URL : https://hal.archives-ouvertes.fr/hal-01224683

]. F. Glover, H. Robbins, S. Monro, ]. J. Neel-]-t, B. Rondeau et al., A stochastic approximation method Synthetic symmetry in cognitive radio networks Cognitive radios with genetic algorithms: Intelligent control of software defined radios, Proc. Forum Tech. Conf . Product Expo. SDR Proc. Forum Tech. Conf. SDR, pp.533-549400, 1951.

]. L. Rabiner-]-t, C. J. Rondeau, T. M. Rieser, C. W. Gallagher, ]. K. Bostian et al., A tutorial on hidden Markov models and selected applications in speech recognition Online modeling of wireless channels with hidden Markov models and channel impulse responses for cognitive radios Cyclostationary approaches to signal detection and classification in cognitive radio, Proc Proc. 2nd IEEE Int. Symp. New Frontiers DySPAN, pp.257-2866, 1989.

]. I. Akbar, W. H. Tranter, ]. A. He, K. Bae, T. Newman et al., Dynamic spectrum allocation in cognitive radio using hidden Markov models: Poisson distributed case A Survey of Artificial Intelligence for Cognitive Radios, Proc. IEE SoutheastCon IEEE Transactions on Vehicular Technology Special Issue on Cognitive Radio, pp.196-201, 2007.

F. Ian, W. Akyildiz, M. C. Lee, S. Vuran, C. Mohanty et al., NeXt Generation/Dynamic Spectrum Access/Cognitive Radio Wireless Networks: A Survey Applications of machine learning to cognitive radio networksPerformance improvement of wireless link reliability in the context of cognitive radio, Computer Networks Journal IEEE Wireless Communications IJCSNS International Journal of Computer Science and Network Security, vol.141201, issue.4, pp.15-22, 2006.