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Neuromorphic Cognitive Systems

A Learning and Memory Centered Approach

  • Book
  • © 2017

Overview

Authors:
  1. Qiang Yu

    1. Institute for Infocomm Research, Singapore, Singapore

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  2. Huajin Tang

    1. College of Computer Science, Sichuan University, Chengdu, China

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  3. Jun Hu

    1. AGI Technologies, Singapore, Singapore

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  4. Kay Tan Chen

    1. Department of Computer Science, City University of Hong Kong, Kowloon Tong, Hong Kong

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  • Discusses the computational principles underlying spike-based information processing and cognitive computation with a specific focus on learning and memory
  • Describes theoretical modeling and analysis as well as practical applications
  • Presents the computational ability of bio-inspired systems and offers insights into the mechanisms by which the nervous system operates
  • Provides theories, concepts, methods and applications
  • Includes supplementary material: sn.pub/extras

Part of the book series: Intelligent Systems Reference Library (ISRL, volume 126)

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Table of contents (8 chapters)

  1. Front Matter

    Pages i-xiv
    Download chapter PDF

  2. Introduction

    • Qiang Yu, Huajin Tang, Jun Hu, Kay Chen Tan
    Pages 1-17

  3. Rapid Feedforward Computation by Temporal Encoding and Learning with Spiking Neurons

    • Qiang Yu, Huajin Tang, Jun Hu, Kay Chen Tan
    Pages 19-41

  4. A Spike-Timing Based Integrated Model for Pattern Recognition

    • Qiang Yu, Huajin Tang, Jun Hu, Kay Chen Tan
    Pages 43-63

  5. Precise-Spike-Driven Synaptic Plasticity for Hetero Association of Spatiotemporal Spike Patterns

    • Qiang Yu, Huajin Tang, Jun Hu, Kay Chen Tan
    Pages 65-87

  6. A Spiking Neural Network System for Robust Sequence Recognition

    • Qiang Yu, Huajin Tang, Jun Hu, Kay Chen Tan
    Pages 89-113

  7. Temporal Learning in Multilayer Spiking Neural Networks Through Construction of Causal Connections

    • Qiang Yu, Huajin Tang, Jun Hu, Kay Chen Tan
    Pages 115-129

  8. A Hierarchically Organized Memory Model with Temporal Population Coding

    • Qiang Yu, Huajin Tang, Jun Hu, Kay Chen Tan
    Pages 131-152

  9. Spiking Neuron Based Cognitive Memory Model

    • Qiang Yu, Huajin Tang, Jun Hu, Kay Chen Tan
    Pages 153-172
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Keywords

About this book

This book presents neuromorphic cognitive systems from a learning and memory-centered perspective. It illustrates how to build a system network of neurons to perform spike-based information processing, computing, and high-level cognitive tasks. It is beneficial to a wide spectrum of readers, including undergraduate and postgraduate students and researchers who are interested in neuromorphic computing and neuromorphic engineering, as well as engineers and professionals in industry who are involved in the design and applications of neuromorphic cognitive systems, neuromorphic sensors and processors, and cognitive robotics.

The book formulates a systematic framework, from the basic mathematical and computational methods in spike-based neural encoding, learning in both single and multi-layered networks, to a near cognitive level composed of memory and cognition. Since the mechanisms for integrating spiking neurons integrate to formulate cognitive functions as in the brain are little understood, studies of neuromorphic cognitive systems are urgently needed.

The topics covered in this book range from the neuronal level to the system level. In the neuronal level, synaptic adaptation plays an important role in learning patterns. In order to perform higher-level cognitive functions such as recognition and memory, spiking neurons with learning abilities are consistently integrated, building a system with encoding, learning and memory functionalities. The book describes these aspects in detail.

Authors and Affiliations

  • Institute for Infocomm Research, Singapore, Singapore

    Qiang Yu

  • College of Computer Science, Sichuan University, Chengdu, China

    Huajin Tang

  • AGI Technologies, Singapore, Singapore

    Jun Hu

  • Department of Computer Science, City University of Hong Kong, Kowloon Tong, Hong Kong

    Kay Tan Chen

Bibliographic Information

  • Book Title: Neuromorphic Cognitive Systems

  • Book Subtitle: A Learning and Memory Centered Approach

  • Authors: Qiang Yu, Huajin Tang, Jun Hu, Kay Tan Chen

  • Series Title: Intelligent Systems Reference Library

  • DOI: https://doi.org/10.1007/978-3-319-55310-8

  • Publisher: Springer Cham

  • eBook Packages: Engineering, Engineering (R0)

  • Copyright Information: Springer International Publishing AG 2017

  • Hardcover ISBN: 978-3-319-55308-5Published: 10 May 2017

  • Softcover ISBN: 978-3-319-85625-4Published: 09 May 2018

  • eBook ISBN: 978-3-319-55310-8Published: 03 May 2017

  • Series ISSN: 1868-4394

  • Series E-ISSN: 1868-4408

  • Edition Number: 1

  • Number of Pages: XIV, 172

  • Topics: Computational Intelligence, Artificial Intelligence, Neurosciences

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