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Emerging Trends in Neuro Engineering and Neural Computation

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Cover of 'Emerging Trends in Neuro Engineering and Neural Computation'

Table of Contents

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    Book Overview
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    Chapter 1 CMOS-Based High-Density Microelectrode Arrays: Technology and Applications
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    Chapter 2 Microelectrode Arrays: Architecture, Challenges and Engineering Solutions
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    Chapter 3 Revolutionizing Causal Circuitry Neurostimulation Utilizing the Optogenetic Technique Through Advanced Microsystems Development
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    Chapter 4 Physiological Monitoring in Deep Brain Stimulation: Toward Closed-Loop Neuromodulation Therapies
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    Chapter 5 Mechanism of Docosahexaenoic Acid in the Enhancement of Neuronal Signalling
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    Chapter 6 Insects Neural Model: Potential Alternate to Mammals for Electrophysiological Studies
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    Chapter 7 Synchronization Criteria for Delay Coupled Izhikevich Neurons
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    Chapter 8 Capturing Cognition via EEG-Based Functional Brain Networks
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    Chapter 9 Modelling of Tumour-Induced Angiogenesis Influenced by Haptotaxis
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    Chapter 10 Noise Reduction in ECG Signals Using Wavelet Transform and Dynamic Thresholding
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    Chapter 11 Development of a Co-evolutionary Radial Basis Function Neural Classifier by a k-Random Opponents Topology
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    Chapter 12 Mining Outliers from Medical Datasets Using Neighbourhood Rough Set and Data Classification with Neural Network
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    Chapter 13 A Modified Functional Link Neural Network for Data Classification
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    Chapter 14 Experimental Study of Elman Network in Temporal Classification
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    Chapter 15 Monotone Data Samples Do Not Always Generate Monotone Fuzzy If-Then Rules
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Chapter title
CMOS-Based High-Density Microelectrode Arrays: Technology and Applications
Chapter number 1
Book title
Emerging Trends in Neuro Engineering and Neural Computation
Published by
Springer Singapore, March 2017
DOI 10.1007/978-981-10-3957-7_1
Book ISBNs
978-9-81-103955-3, 978-9-81-103957-7
Authors

Marie Engelene J. Obien, Wei Gong, Urs Frey, Douglas James Bakkum

Editors

Asim Bhatti, Kendall H. Lee, Hamid Garmestani, Chee Peng Lim

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X Demographics

The data shown below were collected from the profiles of 3 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 16 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 16 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 3 19%
Researcher 3 19%
Student > Postgraduate 2 13%
Student > Doctoral Student 1 6%
Unknown 7 44%
Readers by discipline Count As %
Engineering 5 31%
Biochemistry, Genetics and Molecular Biology 1 6%
Medicine and Dentistry 1 6%
Agricultural and Biological Sciences 1 6%
Unknown 8 50%