Application of FPGA to Real‐Time Machine Learning: Hardware Reservoir Computers and Software Image Processing

Application of FPGA to Real‐Time Machine Learning: Hardware Reservoir Computers and Software Image Processing Front Cover
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2018-07-05
173 pages

Book Description

This book lies at the of – a subfield of that develops for challenging tasks such as shape or image recognition, where traditional fail – and photonics – the physical science of light, which underlies many of the optical communications technologies used in our information society. It provides a thorough introduction to reservoir and field-programmable gate arrays (FPGAs).

Recently, photonic implementations of reservoir computing (a machine learning algorithm based on artificial neural networks) have made a breakthrough in optical computing possible. In this book, the author pushes the performance of these significantly beyond what was achieved before. By interfacing a photonic reservoir computer with a high-speed electronic device (an FPGA), the author successfully interacts with the reservoir computer in real time, allowing him to considerably expand its capabilities and range of possible applications. Furthermore, the author draws on his expertise in machine learning and FPGA programming to make progress on a very different problem, namely the real-time image analysis of optical coherence tomography for atherosclerotic arteries.

Table of Contents

Chapter 1 Introduction
Chapter 2 Online Training Of A Photonic Reservoir Computer
Chapter 3 Backpropagation With Photonics
Chapter 4 Photonic Reservoir Computer With Output Feedback
Chapter 5 Towards Online-Trained Analogue Readout Layer
Chapter 6 Real-Time Automated Tissue Characterisation For Intravascular Oct Scans
Chapter 7 Conclusion And Perspectives

Book Details

  • Title: Application of FPGA to Real‐Time Machine Learning: Hardware Reservoir Computers and Software Image Processing
  • Author:
  • Length: 173 pages
  • Edition: 1st ed. 2018
  • Language: English
  • Publisher:
  • Publication Date: 2018-07-05
  • ISBN-10: 3319910523
  • ISBN-13: 9783319910529
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