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Computational Neuroscience

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Cover of 'Computational Neuroscience'

Table of Contents

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    Book Overview
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    Chapter 1 A Network of Spiking Neurons Performing a Relational Categorization Task
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    Chapter 2 Chaotic Synchronization of Neural Networks in FPGA
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    Chapter 3 Assessing the Performance of Convolutional Neural Networks on Classifying Disorders in Apple Tree Leaves
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    Chapter 4 Towards Graffiti Classification in Weakly Labeled Images Using Convolutional Neural Networks
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    Chapter 5 Computational Models for the Propagation of Spreading Depression Waves
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    Chapter 6 How Artificial Intelligence is Supporting Neuroscience Research: A Discussion About Foundations, Methods and Applications
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    Chapter 7 Investigating Crime Rate Prediction Using Street-Level Images and Siamese Convolutional Neural Networks
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    Chapter 8 Developing of a Video-Based Model for UAV Autonomous Navigation
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    Chapter 9 Cyberbullying Classification Using Extreme Learning Machine Applied to Portuguese Language
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    Chapter 10 Pseudorehearsal Approach for Incremental Learning of Deep Convolutional Neural Networks
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    Chapter 11 A Brain Computer Interface Using VEP and MMSC for Driving a Mechanical Arm
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    Chapter 12 An Adaptive User Interface Based on Psychological Test and Task-Relevance
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    Chapter 13 Decision Tree to Analyses EEG Signal: A Case Study Using Spatial Activities
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    Chapter 14 Multi-Network-Feedback-Error-Learning with Automatic Insertion: Validation to a Nonlinear System
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    Chapter 15 Planned Obsolescence Using Nanotechnology for Protection Against Artificial Intelligence
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Title
Computational Neuroscience
Published by
Springer, Cham, January 2017
DOI 10.1007/978-3-319-71011-2
ISBNs
978-3-31-971010-5, 978-3-31-971011-2
Editors

Dante Augusto Couto Barone, Eduardo Oliveira Teles, Christian Puhlmann Brackmann

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