Neural Information Processing, Tingwen Huang; Zhigang Zeng; Chuandong Li; Chi Sin

Автор: Monica Bianchini; Marco Maggini; Lakhmi C. Jain
Название: Handbook on Neural Information Processing
ISBN: 3642429890 ISBN-13(EAN): 9783642429897
Издательство: Springer
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Цена: 139310.00 T
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This handbook presents some of the most recent topics in neural information processing, covering both theoretical concepts and practical applications. The contributions include:

• Deep architectures
• Recurrent, recursive, and graph neural networks
• Cellular neural networks
• Bayesian networks
• Approximation capabilities of neural networks
• Semi-supervised learning
• Statistical relational learning
• Kernel methods for structured data
• Multiple classifier systems
• Self organisation and modal learning
• Applications to content-based image retrieval, text mining in large document collections, and bioinformatics

This book is thought particularly for graduate students, researchers and practitioners, willing to deepen their knowledge on more advanced connectionist models and related learning paradigms.

Автор: Bianchini Monica
Название: Handbook on Neural Information Processing
ISBN: 3642366562 ISBN-13(EAN): 9783642366567
Издательство: Springer
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Цена: 174150.00 T
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Neural Network Architectures.- Learning paradigms.-

Reasoning and applications.- conclusions.

Reasoning and applications.- conclusions.

Автор: Chi-Sing Leung; Minho Lee; Jonathan H. Chan
Название: Neural Information Processing
ISBN: 3642106765 ISBN-13(EAN): 9783642106767
Издательство: Springer
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Цена: 144410.00 T
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Описание: th This two-volume set constitutes the Proceedings of the 16 International Conference on Neural Information Processing (ICONIP 2009), held in Bangkok, Thailand, during December 1-5, 2009.

Автор: Chi-Sing Leung; Minho Lee; Jonathan H. Chan
Название: Neural Information Processing
ISBN: 364210682X ISBN-13(EAN): 9783642106828
Издательство: Springer
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Цена: 144410.00 T
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Описание: th This two-volume set constitutes the Proceedings of the 16 International Conference on Neural Information Processing (ICONIP 2009), held in Bangkok, Thailand, during December 1-5, 2009.

Автор: Hirose
Название: Neural Information Processing
ISBN: 3319466801 ISBN-13(EAN): 9783319466804
Издательство: Springer
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Цена: 91310.00 T
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Описание: The four volume set LNCS 9947, LNCS 9948, LNCS 9949, and LNCS 9950 constitues the proceedings of the 23rd International Conference on Neural Information Processing, ICONIP 2016, held in Kyoto, Japan, in October 2016. big data analysis; neural data analysis; data mining and cybersecurity workshop; data mining;

Автор: Hirose
Название: Neural Information Processing
ISBN: 3319466712 ISBN-13(EAN): 9783319466712
Издательство: Springer
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Цена: 91310.00 T
Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: The four volume set LNCS 9947, LNCS 9948, LNCS 9949, and LNCS 9950 constitues the proceedings of the 23rd International Conference on Neural Information Processing, ICONIP 2016, held in Kyoto, Japan, in October 2016. big data analysis; neural data analysis; data mining and cybersecurity workshop; data mining;

Автор: Hirose
Название: Neural Information Processing
ISBN: 3319466860 ISBN-13(EAN): 9783319466866
Издательство: Springer
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Цена: 83850.00 T
Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: The four volume set LNCS 9947, LNCS 9948, LNCS 9949, and LNCS 9950 constitutes the proceedings of the 23rd International Conference on Neural Information Processing, ICONIP 2016, held in Kyoto, Japan, in October 2016. big data analysis; neural data analysis; data mining and cybersecurity workshop; data mining;

Автор: Hirose
Название: Neural Information Processing
ISBN: 3319466747 ISBN-13(EAN): 9783319466743
Издательство: Springer
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Цена: 83850.00 T
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Описание: The four volume set LNCS 9947, LNCS 9948, LNCS 9949, and LNCS 9950 constitues the proceedings of the 23rd International Conference on Neural Information Processing, ICONIP 2016, held in Kyoto, Japan, in October 2016. big data analysis; neural data analysis; data mining and cybersecurity workshop; data mining;

Автор: Werner v. Seelen; Konstantin Behrend
Название: Principles of Neural Information Processing
ISBN: 3319201123 ISBN-13(EAN): 9783319201122
Издательство: Springer
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Цена: 95770.00 T
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In this fundamental book the authors devise a framework that describes the working of the brain as a whole. It presents a comprehensive introduction to the principles of Neural Information Processing as well as recent and authoritative research. The books guiding principles are the main purpose of neural activity, namely, to organize behavior to ensure survival, as well as the understanding of the evolutionary genesis of the brain. Among the developed principles and strategies belong self-organization of neural systems, flexibility, the active interpretation of the world by means of construction and prediction as well as their embedding into the world, all of which form the framework of the presented description. Since, in brains, their partial self-organization, the lifelong adaptation and their use of various methods of processing incoming information are all interconnected, the authors have chosen not only neurobiology and evolution theory as a basis for the elaboration of such a framework but also systems and signal theory.

The most important message of the book and authors is: brains are evolved as a whole and a description of parts although necessary lets one miss the wood for the trees.

Автор: Derong Liu; Shengli Xie; Yuanqing Li; Dongbin Zhao
Название: Neural Information Processing
ISBN: 3319700898 ISBN-13(EAN): 9783319700892
Издательство: Springer
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Цена: 111790.00 T
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Описание: The six volume set LNCS 10634, LNCS 10635, LNCS 10636, LNCS 10637, LNCS 10638, and LNCS 10639 constitues the proceedings of the 24rd International Conference on Neural Information Processing, ICONIP 2017, held in Guangzhou, China, in November 2017.

Автор: Derong Liu; Shengli Xie; Yuanqing Li; Dongbin Zhao
Название: Neural Information Processing
ISBN: 3319700952 ISBN-13(EAN): 9783319700953
Издательство: Springer
Рейтинг:
Цена: 111790.00 T
Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: The six volume set LNCS 10634, LNCS 10635, LNCS 10636, LNCS 10637, LNCS 10638, and LNCS 10639 constituts the proceedings of the 24rd International Conference on Neural Information Processing, ICONIP 2017, held in Guangzhou, China, in November 2017.

Автор: Chu Kiong Loo; Yap Keem Siah; Kok Wai Wong; Andrew
Название: Neural Information Processing
ISBN: 3319126369 ISBN-13(EAN): 9783319126364
Издательство: Springer
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Цена: 74530.00 T
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Описание: Cognitive Science.-Transfer Entropy and Information Flow Patterns in Functional Brain Networks during Cognitive Activity.- Human Implicit Intent Discrimination Using EEG and Eye Movement.- Towards Establishing Relationships Between Human Arousal level and Motion Mass.- Estimating Nonlinear Spatiotemporal Membrane Dynamics in Active Dendrites.- Inter Subject Correlation of Brain Activity during Visuo-Motor Sequence Learning.- An Agent Response System based on Mirror Neuron and Theory of Mind.- Dynamic of Nitric Oxide Diffusion in Volume Transmission: Model and Validation.- A Computational Model of the Relation Between Regulation of Negative Emotions and Mood.- Neural Networks and Learning Systems - Theory and Design.- Low-cost Representation for Restricted Boltzmann Machines.- Add-if-Silent Rule for Training Multi-layered Convolutional Network Neocognitron.- Posterior Distribution Learning (PDL): A Novel Supervised Learning Framework Including Unlabeled Samples Distribution into Decision.- Computational Model of Neocortical Learning Process: Prototype.- Active Learning with Maximum Density and Minimum Redundancy.- One-to-Many Association Ability of Chaotic Quaternionic Multidirectional Associative Memory.- An Entropy-guided Adaptive Co-construction Method of State and Action Spaces in Reinforcement Learning.- A Nodes Reduction Procedure for RBFNDDA through Histogram.- Toroidal approximate identity neural networks are universal approximators.- Self-Organizing Neural Grove.- Transfer learning using the Online FMM model.- A supervised methodology to measure the variables contribution to a clustering.- Coupling between spatial consistency of neural ring and local eld potential coherence: A computational study.- Fading channel prediction based on self-optimizing neural networks.- Invariant Multiparameter Sensitivity of Oscillator Network.- Spatial-Temporal Saliency Feature Extraction For Robust Mean-Shift Tracker.- BOOSTRON: Boosting Based Perceptron Learning.- G-Stream: Growing Neural Gas over Data Stream.- Combining Active Learning and Semi-Supervised Learning Using Local and Global Consistency.- Complex-Valued Neural Networks -- Recent Progress and Future Directions.- A Cascade System of Simple Dynamic Binary Neural Networks and Its Sparsification.- A Model of V4 Neurons Based on Sparse Coding.- A fast and memory-efficient hierarchical graph clustering algorithm.- Hopfield-Type Associative Memory with Sparse Modular Networks.- Concept Drift Detection based on Anomaly Analysis.- Online learning for faulty RBF networks with the concurrent fault.- The Performance of the Stochastic DNN-kWTA network.- Modularity maximization adjusted by neural networks.- A dynamic pruning strategy for incremental learning on a budget.- Neural Computing with Concurrent Synchrony.- A Line-partitioned Heteroassociative Memory for Storing Binary Fresnel Hologram.- A Unified Framework for Privacy Preserving Data Clustering.- Spiking Neural Network with Lateral Inhibition for Reward-based Associative Learning.- Fuzzy Signature Neural Networks for Classification: Optimising the Structure.- Self-Organizing Map-based Probabilistic Associative Memory.- Neural Networks and Learning Systems - Applications.- A Causal Model for Disease Pathway Discovery.- Enhanced Non-linear Features for On-line Handwriting Recognition Using Deep Learning.- Recognizing Human Actions by Using the Evolving Remote Supervised Method of Spiking Neural Networks.- A Neural Networks Committee for the Contextual Bandit Problem.- Multi-step Predictions of Landslide Displacements based on Echo State Network.- Discrete-Time Nonlinear Generalized Policy Iteration for Optimal Control Using Neural Networks.- ANFIS-Based Model for Improved Paraphrase Rating Prediction.- Contextual Bandit for Active Learning: Active Thompson Sampling.- Choosing the Best Auto-encoder-based Bagging Classifier: An Empirical Study.- Classification of fMRI Data in the NeuCube Evolving Spiking Neural Ne