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Evolutionary programming (Computer science) --- Evolutionary computation. --- Programmation évolutive --- Réseaux neuronaux à structure évolutive --- Agrotechnology and Food Sciences. Information and Communication Technology --- Information and Communication Technology (General) --- Evolutionary programming (Computer science). --- Information and Communication Technology (General). --- Programmation évolutive --- Réseaux neuronaux à structure évolutive --- Evolutionary computation

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This volume contains the papers presented at the 7th International Conference on Independent Component Analysis (ICA) and Source Separation held in L- don, 9–12 September 2007, at Queen Mary, University of London. Independent Component Analysis and Signal Separation is one of the most exciting current areas of research in statistical signal processing and unsup- vised machine learning. The area has received attention from several research communities including machine learning, neural networks, statistical signal p- cessing and Bayesian modeling. Independent Component Analysis and Signal Separation has applications at the intersection of many science and engineering disciplinesconcernedwithunderstandingandextractingusefulinformationfrom data as diverse as neuronal activity and brain images, bioinformatics, com- nications, the World Wide Web, audio, video, sensor signals, or time series. This year’s event was organized by the EPSRC-funded UK ICA Research Network (www.icarn.org). There was also a minor change to the conference title this year with the exclusion of the word‘blind’. The motivation for this was the increasing number of interesting submissions using non-blind or semi-blind techniques that did not really warrant this label. Evidence of the continued interest in the ?eld was demonstrated by the healthy number of submissions received, and of the 149 papers submitted just over two thirds were accepted.

Signal processing --- Blind source separation --- Neural networks (Computer science) --- Electronic noise --- Multivariate analysis --- Traitement du signal --- Réseaux neuronaux (Informatique) --- Bruit électronique --- Analyse multivariée --- Digital techniques --- Congresses. --- Techniques numériques --- Congrès --- Independent component analysis --- Telecommunications --- Computer Science --- Electrical & Computer Engineering --- Engineering & Applied Sciences --- Blind signal separation --- BSS (Blind source separation) --- Computer science. --- Coding theory. --- Computers. --- Algorithms. --- Data mining. --- Statistics. --- Computer Science. --- Algorithm Analysis and Problem Complexity. --- Computation by Abstract Devices. --- Coding and Information Theory. --- Statistics and Computing/Statistics Programs. --- Data Mining and Knowledge Discovery. --- Signal, Image and Speech Processing. --- Statistical analysis --- Statistical data --- Statistical methods --- Statistical science --- Mathematics --- Econometrics --- Algorithmic knowledge discovery --- Factual data analysis --- KDD (Information retrieval) --- Knowledge discovery in data --- Knowledge discovery in databases --- Mining, Data --- Database searching --- Algorism --- Algebra --- Arithmetic --- Automatic computers --- Automatic data processors --- Computer hardware --- Computing machines (Computers) --- Electronic brains --- Electronic calculating-machines --- Electronic computers --- Hardware, Computer --- Computer systems --- Cybernetics --- Machine theory --- Calculators --- Cyberspace --- Data compression (Telecommunication) --- Digital electronics --- Information theory --- Signal theory (Telecommunication) --- Computer programming --- Informatics --- Science --- Foundations --- Source separation (Signal processing) --- Computer software. --- Mathematical statistics. --- Statistical inference --- Statistics, Mathematical --- Statistics --- Probabilities --- Sampling (Statistics) --- Software, Computer --- Information theory. --- Statistics . --- Signal processing. --- Image processing. --- Speech processing systems. --- Computational linguistics --- Electronic systems --- Modulation theory --- Oral communication --- Speech --- Telecommunication --- Singing voice synthesizers --- Pictorial data processing --- Picture processing --- Processing, Image --- Imaging systems --- Optical data processing --- Processing, Signal --- Information measurement --- Communication theory --- Communication --- Artificial intelligence --- Intelligence artificielle --- Réseaux neuronaux (informatique) --- ICA (Independent component analysis) --- Réseaux neuronaux (informatique) --- Techniques numériques

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We present in this volume the collection of finally accepted papers for the ninth e- tion of the IWANN conference (“International Work-Conference on Artificial Neural Networks”). This biennial meeting focuses on the foundations, theory, models and applications of systems inspired by nature (neural networks, fuzzy logic and evo- tionary systems). Since the first edition of IWANN in Granada (LNCS 540, 1991), the computational intelligence community and the domain itself have matured and evolved. Under the computational intelligent banner we find a very heterogeneous scenario with a main interest and objective: to better understand nature and natural entities for the correct elaboration of theories, models and new algorithms. For scientifics, engineers and professionals working in the area, this is a very good way to get real, solid and c- petitive applications. More and more, these new computational techniques are used in applications that try to bring a new situation of well-being to the user. The conjunction of a more and more miniaturized hardware together with the growing computational intelligence embodied in this hardware leads us towards fully integrated embedded systems-on- chip and opens the door for truly ubiquitous electronics.

Neural networks (Neurobiology) --- Neural networks (Computer science) --- Connectionism --- Artificial intelligence --- Cognitive neuroscience --- Réseaux neuronaux (Neurobiologie) --- Réseaux neuronaux (Informatique) --- Intelligence artificielle --- Neurosciences cognitives --- Congresses. --- Congrès --- Computer Science --- Engineering & Applied Sciences --- Connexionism --- Computer science. --- Computers. --- Algorithms. --- Artificial intelligence. --- Image processing. --- Pattern recognition. --- Bioinformatics. --- Computer Science. --- Artificial Intelligence (incl. Robotics). --- Computation by Abstract Devices. --- Algorithm Analysis and Problem Complexity. --- Image Processing and Computer Vision. --- Pattern Recognition. --- Computational Biology/Bioinformatics. --- Bio-informatics --- Biological informatics --- Biology --- Information science --- Computational biology --- Systems biology --- Design perception --- Pattern recognition --- Form perception --- Perception --- Figure-ground perception --- Pictorial data processing --- Picture processing --- Processing, Image --- Imaging systems --- Optical data processing --- AI (Artificial intelligence) --- Artificial thinking --- Electronic brains --- Intellectronics --- Intelligence, Artificial --- Intelligent machines --- Machine intelligence --- Thinking, Artificial --- Bionics --- Cognitive science --- Digital computer simulation --- Electronic data processing --- Logic machines --- Machine theory --- Self-organizing systems --- Simulation methods --- Fifth generation computers --- Neural computers --- Algorism --- Algebra --- Arithmetic --- Automatic computers --- Automatic data processors --- Computer hardware --- Computing machines (Computers) --- Electronic calculating-machines --- Electronic computers --- Hardware, Computer --- Computer systems --- Cybernetics --- Calculators --- Cyberspace --- Informatics --- Science --- Data processing --- Foundations --- Cognition --- Computer software. --- Computer vision. --- Optical pattern recognition. --- Artificial Intelligence. --- Pattern perception --- Perceptrons --- Visual discrimination --- Machine vision --- Vision, Computer --- Image processing --- Pattern recognition systems --- Software, Computer --- Optical data processing. --- Optical computing --- Visual data processing --- Integrated optics --- Photonics --- Computers --- Optical equipment --- Industrial applications --- Artificial neural networks --- Nets, Neural (Computer science) --- Networks, Neural (Computer science) --- Neural nets (Computer science) --- Natural computation --- Soft computing --- Pattern recognition systems. --- Theory of Computation. --- Computer Vision. --- Automated Pattern Recognition. --- Computational and Systems Biology. --- Pattern classification systems --- Pattern recognition computers --- Computer vision

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This book is devoted to the application of genetic algorithms in continuous global optimization. Some of their properties and behavior are highlighted and formally justified. Various optimization techniques and their taxonomy are the background for detailed discussion. The nature of continuous genetic search is explained by studying the dynamics of probabilistic measure, which is utilized to create subsequent populations. This approach shows that genetic algorithms can be used to extract some areas of the search domain more effectively than to find isolated local minima. The biological metaphor of such behavior is the whole population surviving by rapid exploration of new regions of feeding rather than caring for a single individual. One group of strategies that can make use of this property are two-phase global optimization methods. In the first phase the central parts of the basins of attraction are distinguished by genetic population analysis. Afterwards, the minimizers are found by convex optimization methods executed in parallel.

Genetic algorithms --- Evolutionary computation. --- Combinatorial optimization. --- Réseaux neuronaux à structure évolutive --- Optimisation combinatoire --- Mathematical models. --- Data processing. --- Genetic algorithms -- Data processing. --- Genetic algorithms -- Mathematical models. --- Combinatorial optimization, --- Evolutionary computation --- Engineering & Applied Sciences --- Civil & Environmental Engineering --- Operations Research --- Civil Engineering --- Computer Science --- Applied Mathematics --- Data processing --- Optimization, Combinatorial --- Computation, Evolutionary --- GAs (Algorithms) --- Genetic searches (Algorithms) --- Engineering. --- Artificial intelligence. --- Applied mathematics. --- Engineering mathematics. --- Appl.Mathematics/Computational Methods of Engineering. --- Artificial Intelligence (incl. Robotics). --- Engineering --- Engineering analysis --- Mathematical analysis --- AI (Artificial intelligence) --- Artificial thinking --- Electronic brains --- Intellectronics --- Intelligence, Artificial --- Intelligent machines --- Machine intelligence --- Thinking, Artificial --- Bionics --- Cognitive science --- Digital computer simulation --- Electronic data processing --- Logic machines --- Machine theory --- Self-organizing systems --- Simulation methods --- Fifth generation computers --- Neural computers --- Construction --- Industrial arts --- Technology --- Mathematics --- Combinatorial analysis --- Mathematical optimization --- Neural networks (Computer science) --- Algorithms --- Combinatorial optimization --- Genetic programming (Computer science) --- Learning classifier systems --- Mathematical and Computational Engineering. --- Artificial Intelligence.

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Evolutionary scheduling is a vital research domain at the interface of two important sciences - artificial intelligence and operational research. Scheduling problems are generally complex, large scale, constrained, and multi-objective in nature, and classical operational research techniques are often inadequate at solving them effectively. With the advent of computation intelligence, there is renewed interest in solving scheduling problems using evolutionary computational techniques. These techniques, which include genetic algorithms, genetic programming, evolutionary strategies, memetic algorithms, particle swarm optimization, ant colony systems, etc, are derived from biologically inspired concepts and are well-suited to solve scheduling problems since they are highly scalable and flexible in terms of handling constraints and multiple objectives. This edited book gives an overview of many of the current developments in the large and growing field of evolutionary scheduling, and demonstrates the applicability of evolutionary computational techniques to solve scheduling problems, not only to small-scale test problems, but also fully-fledged real-world problems. The intended readers of this book are engineers, researchers, practitioners, senior undergraduates, and graduate students who are interested in the field of evolutionary scheduling.

Evolutionary computation. --- Computer scheduling. --- Computational intelligence. --- Réseaux neuronaux à structure évolutive --- Ordonnancement (Informatique) --- Intelligence informatique --- Evolutionary computation --- Computer scheduling --- Computational intelligence --- Applied Mathematics --- Civil Engineering --- Computer Science --- Civil & Environmental Engineering --- Engineering & Applied Sciences --- Intelligence, Computational --- Electronic data processing --- Processor scheduling (Electronic data processing) --- Scheduling of electronic data processing --- Computation, Evolutionary --- Scheduling --- Computer science. --- Artificial intelligence. --- Applied mathematics. --- Engineering mathematics. --- Computer Science. --- Artificial Intelligence (incl. Robotics). --- Appl.Mathematics/Computational Methods of Engineering. --- Production scheduling --- Time-sharing computer systems --- Neural networks (Computer science) --- Artificial intelligence --- Soft computing --- Artificial Intelligence. --- Mathematical and Computational Engineering. --- Engineering --- Engineering analysis --- Mathematical analysis --- AI (Artificial intelligence) --- Artificial thinking --- Electronic brains --- Intellectronics --- Intelligence, Artificial --- Intelligent machines --- Machine intelligence --- Thinking, Artificial --- Bionics --- Cognitive science --- Digital computer simulation --- Logic machines --- Machine theory --- Self-organizing systems --- Simulation methods --- Fifth generation computers --- Neural computers --- Mathematics