Brain-Inspired Information Technology

Brain-Inspired Information Technology

Εμφάνιση άλλων εκδόσεων (1)

Λεπτομέρειες βιβλιογραφικής εγγραφής
Κύριος συγγραφέας:	Hanazawa, Akitoshi
Συγγραφή απο Οργανισμό/Αρχή:	SpringerLink (Online service)
Άλλοι συγγραφείς:	Miki, Tsutom, Horio, Keiichi
Μορφή:	Ηλεκτρονική πηγή Εργαλειοθήκη Βιβλίο
Γλώσσα:	English
Έκδοση:	Berlin, Heidelberg Springer-Verlag Berlin Heidelberg 2010
Σειρά:	Studies in Computational Intelligence 266
Θέματα:	Engineering Neurosciences Engineering mathematics Appl.Mathematics/Computational Methods of Engineering Artificial Intelligence (incl. Robotics) Τεχνητή νοημοσύνη
Διαθέσιμο Online:	http://dx.doi.org/10.1007/978-3-642-04025-2

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Neuro-Fuzzy Associative Machinery for Comprehensive Brain and Cognition Modelling
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Advances in Intelligent Information Systems
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The Brain: Fuzzy Arithmetic to Quantum Computing
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Neural Networks: Computational Models and Applications
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Trends in Neural Computation
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Perception-based Data Mining and Decision Making in Economics and Finance
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Artificial Intelligence in Recognition and Classification of Astrophysical and Medical Images
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Fundamentals of Relational Database Management Systems
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Evolutionary Scheduling
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Emergent Intelligence of Networked Agents
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Recent Advances in Memetic Algorithms
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Genetic Systems Programming Theory and Experiences
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Innovations in Machine Learning Theory and Applications
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Complex-Valued Neural Networks
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Parallel and Distributed Logic Programming Towards the Design of a Framework for the Next Generation Database Machines
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Swarm Intelligent Systems
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Scalable Optimization via Probabilistic Modeling
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Swarm Intelligence in Data Mining
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Mining of Data with Complex Structures
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Uncertainty Approaches for Spatial Data Modeling and Processing A Decision Support Perspective
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Quality Measures in Data Mining
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Intelligent Educational Machines Methodologies and Experiences
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Mobile Robots: The Evolutionary Approach
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Applied Graph Theory in Computer Vision and Pattern Recognition
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Parameter Setting in Evolutionary Algorithms
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Kernel Based Algorithms for Mining Huge Data Sets Supervised, Semi-supervised, and Unsupervised Learning
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Advances in Evolutionary Algorithms Theory, Design and Practice
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Logical Foundations for Rule-Based Systems
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Parallel Evolutionary Computations
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