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Optical Signal Processing, Computing, and Neural Networks
Frances T. S. Yu
Suganda Jutamulia
出版
Wiley
, 1992-11-19
主題
Computers / Data Science / Neural Networks
Computers / Optical Data Processing
Technology & Engineering / Electrical
Technology & Engineering / Imaging Systems
Technology & Engineering / Signals & Signal Processing
ISBN
0471536547
9780471536543
URL
http://books.google.com.hk/books?id=4PRRAAAAMAAJ&hl=&source=gbs_api
註釋
In recent years, optical computing and optical neural networks research has enriched the field originally known as optical signal processing. Optical Signal Processing, Computing, and Neural Networks is a self-contained textbook that offers an introductory survey which examines photonics, linear and nonlinear signal processing, and numerical, symbolic, and neural computing. This comprehensive sourcebook is a basic text for students who lack an intensive background in optic, electromagnetic, computer, and neural network theories. It will also serve as a working reference for optical physicists and engineers involved in current research and development of modern optical signal processing that includes optical computing and neural networks. The first chapter of this book contains the basic coherent theory and concepts of optical transformation. The second chapter introduces the fundamental concept of optical signal processing and its architectures. The third chapter presents selected applications in coherent optics while the fourth chapter discusses white-light processing and its applications. The advances of spatial-light modulators are discussed as well as hybrid-optical architectures using spatial-light modulators in later chapters. Applications of photorefractive crystals in optical signal processing are presented in chapter 7. Digital-optical computing is described in chapter 8 while optical neural networks and their architectures, designs, and models are thoroughly covered in chapter 9. Examples and experimental results are included throughout the book to emphasize the concepts. Chapters include problem sets, 330 throughout, that reinforce key elements in the text.
