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The two volume set LNCS 4221 and LNCS 4222 constitutes the refereed proceedings of the Second International Conference on Natural Computation, ICNC 2006, held in Xi'an, China, in September 2006 as a joint event in federation with the Third International Conference on Fuzzy Systems and Knowledge Discovery FSKD 2006 (LNAI 4223). After a demanding review process 168 carefully revised full papers and 86 revised short papers were selected from 1915 submissions for presentation in two volumes. The first volume includes 130 papers related to artificial neural networks, natural neural systems and cognitive science, neural network applications, as well as evolutionary computation: theory and algorithms. The 124 papers in the second volume are orgainzed in topical sections on other topics in natural computation, natural computation techniques applications, hardware, and cross-disciplinary topics.
This is volume I of the proceedings of the Second International Conference on Natural Computation, ICNC 2006. After a demanding review process 168 carefully revised full papers and 86 revised short papers were selected from 1915 submissions for presentation in two volumes. This first volume includes 130 papers related to artificial neural networks, natural neural systems and cognitive science, neural network applications, as well as evolutionary computation: theory and algorithms.
The International Conference on Computational Intelligence and Security (CIS) is an annualinternationalconference that bringstogether researchers, engineers, developers and practitioners from both academia and industry to share expe- ence and exchange and cross-fertilize ideas on all areas of computational - telligence and information security. The conference serves as a forum for the dissemination of state-of-the-art research and the development, and implem- tationsof systems, technologiesandapplicationsinthese two broad, interrelated ?elds. This year CIS 2005 was co-organized by the IEEE (Hong Kong) Com- tational Intelligence Chapter and Xidian University, and co-sponsored by Hong Kong Baptist University, National Natural Science Foundation of China, Key Laboratory of Computer Networks and Information Security of the Ministry of EducationofChina, andGuangdongUniversityofTechnology. CIS2005received in total 1802 submissions from 41 countries and regions all over the world. All of them were strictly peer reviewed by the Program Committee and experts in the ?eld. Finally, 337 high-quality papers were accepted yielding an acc- tance rate of 18. 7%. Among them, 84 papers are the extended papers and 253 are the regular papers. The conference was greatly enriched by a wide range of topics covering all areas of computational intelligence and information security. Furthermore, tutorials and workshops were held for discussions of the proposed ideas. Such practice is extremely important for the e?ective development of the two ?elds and computer science in general. Wewouldliketothanktheorganizers: theIEEE(HongKong)Computational Intelligence Chapter and Xidian University for their great contributions and - forts in this big e
Brain and Nature-Inspired Learning, Computation and Recognition presents a systematic analysis of neural networks, natural computing, machine learning and compression, algorithms and applications inspired by the brain and biological mechanisms found in nature. Sections cover new developments and main applications, algorithms and simulations. Developments in brain and nature-inspired learning have promoted interest in image processing, clustering problems, change detection, control theory and other disciplines. The book discusses the main problems and applications pertaining to bio-inspired computation and recognition, introducing algorithm implementation, model simulation, and practical application of parameter setting. Readers will find solutions to problems in computation and recognition, particularly neural networks, natural computing, machine learning and compressed sensing. This volume offers a comprehensive and well-structured introduction to brain and nature-inspired learning, computation, and recognition.
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