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The Self-Organizing Map, or Kohonen Map, is one of the most widely used neural network algorithms, with thousands of applications covered in the literature. It was one of the strong underlying factors in the popularity of neural networks starting in the early 80's. Currently this method has been included in a large number of commercial and public domain software packages. In this book, top experts on the SOM method take a look at the state of the art and the future of this computing paradigm. The 30 chapters of this book cover the current status of SOM theory, such as connections of SOM to clustering, classification, probabilistic models, and energy functions. Many applications of the SOM are given, with data mining and exploratory data analysis the central topic, applied to large databases of financial data, medical data, free-form text documents, digital images, speech, and process measurements. Biological models related to the SOM are also discussed.

Artificial intelligence. Robotics. Simulation. Graphics

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This two volume set (LNCS 6791 and LNCS 6792) constitutes the refereed proceedings of the 21th International Conference on Artificial Neural Networks, ICANN 2011, held in Espoo, Finland, in June 2011. The 106 revised full or poster papers presented were carefully reviewed and selected from numerous submissions. ICANN 2011 had two basic tracks: brain-inspired computing and machine learning research, with strong cross-disciplinary interactions and applications.

Information Technology --- Artificial Intelligence --- Computer science. --- Computers. --- Algorithms. --- Artificial intelligence. --- Image processing. --- Pattern recognition. --- Computer Science. --- Artificial Intelligence (incl. Robotics). --- Computation by Abstract Devices. --- Algorithm Analysis and Problem Complexity. --- Pattern Recognition. --- Information Systems Applications (incl. Internet). --- Image Processing and Computer Vision. --- Design perception --- Pattern recognition --- Pictorial data processing --- Picture processing --- Processing, Image --- AI (Artificial intelligence) --- Artificial thinking --- Electronic brains --- Intellectronics --- Intelligence, Artificial --- Intelligent machines --- Machine intelligence --- Thinking, Artificial --- Algorism --- Automatic computers --- Automatic data processors --- Computer hardware --- Computing machines (Computers) --- Electronic calculating-machines --- Electronic computers --- Hardware, Computer --- Informatics --- Form perception --- Perception --- Figure-ground perception --- Imaging systems --- Optical data processing --- Bionics --- Cognitive science --- Digital computer simulation --- Electronic data processing --- Logic machines --- Machine theory --- Self-organizing systems --- Simulation methods --- Fifth generation computers --- Neural computers --- Algebra --- Arithmetic --- Computer systems --- Cybernetics --- Calculators --- Cyberspace --- Science --- Foundations --- Computer software. --- Optical pattern recognition. --- Computer vision. --- Artificial Intelligence. --- Machine vision --- Vision, Computer --- Artificial intelligence --- Image processing --- Pattern recognition systems --- Pattern perception --- Perceptrons --- Visual discrimination --- Software, Computer --- Application software. --- Optical data processing. --- Optical computing --- Visual data processing --- Integrated optics --- Photonics --- Computers --- Application computer programs --- Application computer software --- Applications software --- Apps (Computer software) --- Computer software --- Optical equipment --- Pattern recognition systems. --- Theory of Computation. --- Automated Pattern Recognition. --- Computer and Information Systems Applications. --- Computer Vision. --- Pattern classification systems --- Pattern recognition computers --- Computer vision

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Complex analysis --- Mathematical statistics --- Computer science --- Information systems --- Artificial intelligence. Robotics. Simulation. Graphics --- Computer. Automation --- patroonherkenning --- neuronale netwerken --- beeldverwerking --- ICT (informatie- en communicatietechnieken) --- factoranalyse --- complexe analyse (wiskunde) --- machine learning --- informatica --- informatiesystemen --- KI (kunstmatige intelligentie) --- robots

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In honour of Professor Erkki Oja, one of the pioneers of Independent Component Analysis (ICA), this book reviews key advances in the theory and application of ICA, as well as its influence on signal processing, pattern recognition, machine learning, and data mining. Examples of topics which have developed from the advances of ICA, which are covered in the book are: A unifying probabilistic model for PCA and ICA Optimization methods for matrix decompositions Insights into the FastICA algorithmUnsupervised deep learning Machine vision and image retrieval A review of developments in the t.

Mathematics --- Machine elements

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This two volume set (LNCS 6791 and LNCS 6792) constitutes the refereed proceedings of the 21th International Conference on Artificial Neural Networks, ICANN 2011, held in Espoo, Finland, in June 2011. The 106 revised full or poster papers presented were carefully reviewed and selected from numerous submissions. ICANN 2011 had two basic tracks: brain-inspired computing and machine learning research, with strong cross-disciplinary interactions and applications.

Complex analysis --- Mathematical statistics --- Computer science --- Information systems --- Artificial intelligence. Robotics. Simulation. Graphics --- Computer. Automation --- patroonherkenning --- neuronale netwerken --- beeldverwerking --- ICT (informatie- en communicatietechnieken) --- factoranalyse --- complexe analyse (wiskunde) --- machine learning --- informatica --- informatiesystemen --- KI (kunstmatige intelligentie) --- robots