Advances in imaging and electron physics. Volume 107 /
Advances in Imaging & Electron Physics merges two long-running serials--Advances in Electronics & Electron Physics and Advances in Optical & Electron Microscopy. The series features extended articles on the physics of electron devices (especially semiconductor devices), particle optics a...
Clasificación: | Libro Electrónico |
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Otros Autores: | |
Formato: | Electrónico eBook |
Idioma: | Inglés |
Publicado: |
San Diego ; London :
Academic Press,
�1999.
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Colección: | Advances in imaging and electron physics ;
v. 107 |
Temas: | |
Acceso en línea: | Texto completo Texto completo |
Tabla de Contenidos:
- Front Cover; Advances in Imaging and Electron Physics, Volume 107; Copyright Page; Contents; Contributors; Preface; Chapter 1. Magneto-Transport as a Probe of Electron Dynamics in Open Quantum Dots; I. Introduction; II. Magneto-Transport in Open Quantum Dots: Some Theoretical Considerations; III. Weak-Field Magneto-Transport in Open Quantum Dots: Low-Temperature Properties; IV. Weak-Field Magneto-Transport in Open Quantum Dots: High-Temperature Properties; V. High-Field Magneto-Transport in Open Quantum Dots; VI. Concluding Discussion; References
- Chapter 2. External Optical Feedback Effects in Distributed Feedback Semiconductor LasersI. Introduction; II. Distributed Feedback Laser Fundamentals; III. Experimentally Observed Effects; IV. Theories on Optical Feedback; V. External Optical Feedback Sensitivity; VI. Conclusion; References; Chapter 3. Atomic Scale Strain and Composition Evaluation from High-Resolution Transmission Electron Microscopy Images; I. Introduction; II. Strain-State Analysis; III. Composition Evaluation by Lattice Fringe Analysis; IV. Applications; V. Summary and Discussion of the Atomic Scale Analysis Methods
- Appendix A: List of VariablesChapter 4. Hexagonal Sampling in Image Processing; I. Introduction; II. Image Sampling on a Hexagonal Grid; III. Processor Architecture; IV. Binary Image Processing.; V. Monochrome Image Processing; VI. Conclusions; References; Chapter 5. The Group Representation Network: A General Approach to Invariant Pattern Classification; I. Pattern Classification and the Invariance Problem; II. Group Representation Theory; III. Linear and Nonlinear Concomitants; IV. Adaptivity in Group Representation Networks; V. Practical Considerations and Simulations
- VI. The Computational Power of the Group Representation Network ModelVII. The Group Representation Network and Other Invariant Classification Methods; VIII. Summary and Open Questions; Proof of Theorem III. 1; References; Index