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Home > Mathematics and Science Textbooks > Physics > Optical physics > Optical Signal Processing: Fundamentals
Optical Signal Processing: Fundamentals

Optical Signal Processing: Fundamentals


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About the Book

This work presents background material on modern optical signal processing. Intended for graduate students in electrical engineering, physics, and optical engineering, the book covers the fundamental principles of geometrical and physical optics; propagation in anisotropic media; fibre optics; integrated optics; the electro-optic, acousto-optic and magneto-optic effects; noise and stochastic processes; matched, adaptive, Kalman and lattice filters; two-dimensional signal processing and the ambiguity and Wigner distribution functions. A discussion of non-optical signal processing devices, eg SAW, CCD and digital, is intended to provide an understanding of the advantages of optical signal processing. Relevant mathematics is presented in the appendix.

Table of Contents:
1. Introduction.- 1.1 Why Optical Signal Processing?.- 1.2 Signal Processing: Tools and Applications.- 1.3 Arrangement of the Book.- 1.3.1 Guide for Selective Use of the Book.- 1.3.2 Note on References.- 2. Optics Fundamentals.- 2.1 Maxwell's Equations.- 2.2 Boundary Conditions.- 2.3 Snell's Laws.- 2.4 Total Internal Reflection and Optical Tunneling.- 2.5 Transmission Lines.- 2.6 Reflection and Transmission Coefficients for Electromagnetic Waves.- 2.6.1 Normal Incidence: ?i = 0.- 2.6.2 General Case.- 2.7 Group and Phase Velocity.- 2.7.1 Poynting Vector, Ray Velocity, Phase Velocity, and Group Velocity.- 2.7.2 Goos-Has Laws.- 2.4 Total Internal Reflection and Optical Tunneling.- 2.5 Transmission Lines.- 2.6 Reflection and Transmission Coefficients for Electromagnetic Waves.- 2.6.1 Normal Incidence: ?i = 0.- 2.6.2 General Case.- 2.7 Group and Phase Velocity.- 2.7.1 Poynting Vector, Ray Velocity, Phase Velocity, and Group Velocity.- 2.7.2 Goos-Hanchen Effect.- 2.8 Gaussian Beam Propagation.- 2.9 Geometrical Optics.- 2.9.1 Eikonal Equation.- 2.9.2 Matrix Formulation of Geometrical Optics.- 2.9.3 Gaussian Optics Including Lenses.- 2.9.4 Optical Fiber.- 2.10 Gradient Optical Fiber.- 2.11 Integrated Optics and Step-Index Optical Fibers.- 2.11.1 Electromagnetic Waveguide Solutions.- 2.11.2 Parallel Plate Waveguide: TE Solution.- 2.11.3 Integrated Optics Problem.- 2.11.4 Multimode Group Delay in a Dielectric Waveguide.- 2.11.5 Cylindrical Waveguide.- 2.11.6 Stepped-Index Optical Fiber.- 2.12 Propagation in Anisotropic Media.- 2.12.1 Wave Vector Surface, Phase Velocity Surface, and Ray Velocity Surface.- 2.12.2 Double Refraction.- 2.13 Electro-optic Effect.- 2.13.1 General Discussion.- 2.13.2 Kerr Effect.- 2.13.3 Indirect Electro-optic Effect.- 2.14 The Acousto-optic or Elasto-optic Effect.- 2.14.1 Acousto-optic Coefficients.- 2.14.2 Acousto-optic Interaction: Thin Grating.- 2.14.3 Acousto-optic Interaction: Thick Grating.- 2.14.4 Acousto-optic Interaction Including Light Polarization: Isotropic Solids.- 2.14.5 Bragg Acousto-optic Interaction: Light Polarization Included.- 2.14.6 Bragg Diffraction: Anisotropic Case.- 2.15 Magneto-optics.- 2.15.1 Polarization and the Jones Matrix.- 2.15.2 Optical Activity.- 2.15.3 Magneto-optics: The Faraday Effect, the Voigt Effect and the Kerr Effect.- 2.16 Wave Equation with Source and Boundary.- 2.16.1 Diffraction.- 2.16.2 Solution of the Scalar Wave Equation with Source and Boundary.- 2.16.3 Solution of the Vector Wave Equation with Source and Boundary.- 2.17 Fourier Optics.- 2.17.1 Holography.- Problems.- 3. Signal Processing Fundamentals.- 3.1 Analog Signals and Systems.- 3.1.1 Linear Systems.- 3.1.2 Fourier Transforms and Frequency Response.- 3.1.3 Examples.- 3.1.4 Hilbert Transform and Causality.- 3.1.5 Time-Variant Systems.- 3.2 Discrete Systems.- 3.2.1 Examples.- 3.2.2 Sampling Theorem and Aliasing.- 3.2.3 Frequency Response of a Discrete Time Filter.- 3.3 Noise and Stochastic Processes.- 3.3.1 Linear Systems with Stochastic Input.- 3.3.2 Matched Filters.- 3.3.3 Matched Filters from the Point of View of Maximum Output.- 3.3.4 Matched Filtering of Stochastic Signals.- 3.3.5 Noise and Stochastic Processes: Discrete.- 3.3.6 Matrix Methods.- 3.3.7 Matched Filters: Discrete Case.- 3.4 Filters.- 3.5 Adaptive Filters.- 3.5.1 Linear Mean Squares Estimation.- 3.5.2 Least Mean Squares Adaptive Filters.- 3.5.3 Lattice Filters.- 3.6 Power Spectra Estimation.- 3.6.1 MA Model.- 3.6.2 AR Model.- 3.6.3 ARMA Model.- 3.7 Kalman Filtering.- 3.7.1 State-Space Formulation.- 3.7.2 The Kalman Filter.- 3.7.3 Solution of the Ricatti Equation with Constant Coefficients.- 3.7.4 Square Root Filtering.- 3.8 Two-Dimensional Signal Processing.- 3.8.1 Analog Signals and Systems.- 3.8.2 Linear Systems.- 3.8.3 The Fourier Transform and the Spatial Frequency Response.- 3.8.4 Examples of Fourier Transformation, Imaging, etc..- 3.8.5 Space-Variant Systems.- 3.8.6 Discrete Signals and Matrix Representation.- 3.9 Stochastic Processes: Multidimensional.- 3.9.1 Point Source.- 3.9.2 Partially Coherent Source Distribution.- 3.9.3 Coherent Source.- 3.9.4 Effect of a Mask.- 3.9.5 General Case.- 3.9.6 Coherency Matrix.- 3.10 The Ambiguity Function, Wigner Distribution Function and Triple Correlation.- 3.10.1 The Ambiguity Function.- 3.10.2 Wigner Distribution Function.- 3.10.3 Two-Dimensional Ambiguity and Wigner Distribution Functions.- 3.10.4 Triple and Higher-Order Correlations.- Problems.- 4. Introduction to SAW and CCD Technology.- 4.1 History of CCD and SAW Devices.- 4.1.1 Charge Coupled Devices.- 4.1.2 Surface Acoustic Waves.- 4.2 Why SAWs Became Popular and Useful in the 1960s.- 4.2.1 Bulk Ultrasound Devices.- 4.2.2 Advantages of SAWs.- 4.2.3 SAW Devices.- 4.3 Charge Coupled Devices.- 4.4 Magneto-Static Waves.- 4.4.1 MSW Field Equations and Dispersion Relations.- 4.4.2 MSW Devices.- 4.5 ACT Devices.- 4.6 Comparison of Technologies.- 4.6.1 SAW Technology.- 4.6.2 Bulk Ultrasound Devices.- 4.6.3 Charge Coupled Devices.- 4.6.4 Acoustic Charge Transport.- 4.6.5 Acousto-optics.- 4.6.6 Digital Devices: IC/VHSIC.- Appendices.- A. Matrices.- A.1 The Hamilton-Cayley Theorem.- A.2 Some Definitions.- A.3 Matrix Inversion.- A.4 Gaussian Elimination Method.- A.5 Successive Orthogonalization of a Matrix.- A.6 Circulant Matrices and Fourier Matrices.- A.7 Pseudo-Inverse, Singular-Value Decomposition, Overdetermination and Principle of Least Squares: Kalman Filtering.- A.8 Coordinate Transformation.- B. Orthogonal Functions and Polynomials.- B.1 Sturm-Liouville Equation.- B.2 Fourier Series.- B.3 Hypergeometric Series.- B.4 Legendre Polynomials.- B.5 Hermite Polynomials.- B.6 Laguerre Polynomials.- B.7 Generalized Laguerre Polynomials.- B.8 Chebyshev Polynomials.- B.9 Bessel Functions.- C. Principle of Stationary Phase.- D. Vectors.- D.1 Important Results.- D.2 Green's Theorem: Scalar.- D.3 Green's Theorem: Vector.- E. Symmetry Properties of Different Coefficients in Crystal Classes.- References.


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Product Details
  • ISBN-13: 9783540514763
  • Publisher: Springer-Verlag Berlin and Heidelberg GmbH & Co. KG
  • Publisher Imprint: Springer-Verlag Berlin and Heidelberg GmbH & Co. K
  • Height: 235 mm
  • Returnable: N
  • Weight: 875 gr
  • ISBN-10: 3540514767
  • Publisher Date: /04/1991
  • Binding: Hardback
  • Language: English
  • Sub Title: Fundamentals
  • Width: 155 mm


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