Photonic Reservoir Computing : Optical Recurrent Neural Networks / Daniel Brunner, Guy Van der Sande, Miguel C. Soriano.

Format:

Book

Contributor:

Brunner, Daniel, Editor.

Soriano, Miguel C., Editor.

Van der Sande, Guy, Editor.

Language:

English

Subjects (All):

Photonics.

Physical Description:

1 online resource (xii, 264 pages) : illustrations

Place of Publication:

Berlin ; Boston : De Gruyter, [2019]

Language Note:

In English.

Summary:

Photonics has long been considered an attractive substrate for next generation implementations of machine-learning concepts. Reservoir Computing tremendously facilitated the realization of recurrent neural networks in analogue hardware. This concept exploits the properties of complex nonlinear dynamical systems, giving rise to photonic reservoirs implemented by semiconductor lasers, telecommunication modulators and integrated photonic chips.

Contents:

Frontmatter

Preface

Contents

List of Contributing Authors

1. Introduction to novel photonic computing

2. Information processing and computation with photonic reservoir systems

3. Integrated on-chip reservoirs

4. Large scale spatiotemporal reservoirs

5. Time delay systems for reservoir computing

6. Ikeda delay dynamics as Reservoir processors

7. Semiconductor lasers as reservoir substrates

8. Advanced reservoir computers: analogue autonomous systems and real time control

Outlook

Index

Notes:

Description based on online resource; title from PDF title page (publisher's Web site, viewed 06. Apr 2020)

ISBN:

3-11-058211-2

3-11-058349-6

OCLC:

1110714760