| ISBN13: | 9781032618005 |
| ISBN10: | 10326180011 |
| Kötéstípus: | Keménykötés |
| Terjedelem: | 284 oldal |
| Méret: | 234x156 mm |
| Súly: | 453 g |
| Nyelv: | angol |
| Illusztrációk: | 59 Illustrations, black & white; 59 Illustrations, color; 3 Halftones, black & white; 29 Halftones, color; 56 Line drawings, black & white; 30 Line drawings, color; 1 Tables, black & white |
| 700 |
Anisotropy of Metamaterials
GBP 125.00
Kattintson ide a feliratkozáshoz
Anisotropy of Metamaterials: Beyond Conventional Paradigms provides a comprehensive introduction to the mathematical modelling of metamaterials based on the macroscopic complex-valued permittivity tensor of dispersed random composites.
Anisotropy of Metamaterials: Beyond Conventional Paradigms provides a comprehensive introduction to the mathematical modeling of metamaterials based on the macroscopic complex-valued permittivity tensor of dispersed random composites. Key topics include physical and mathematical theory, computer simulations, constructive homogenization, classification of dispersed random composites and their applications in cancer recognition. Image processing and machine learning algorithms are used. The book also discusses the precision of various effective medium approximations, including Bruggeman and Maxwell-Garnett formulas. New analytical, approximate and exact formulas and bounds for the macroscopic permittivity and piezoelectric constants of composites are derived. This book is a valuable tool for academics and professionals in photonics, presenting sustainable materials for sensing, health diagnostics and cancer detection methodologies.
Key features:
- Offers key insights into the current trends and techniques in the study of the macroscopic properties of metamaterials, aiming at stimulating new avenues of research.
- Presents examples of image analysis, the primary tool for non-destructive metamaterials analysis.
- Discusses the applications of Machine Learning to image processing, illustrated using specific code in Python programming language.
Preface. About the authors. Section 1: Physics of metamaterials. Chapter 1: Electromagnetics of metamaterials. Section 2: Mathematical model of complex permittivity in composites. Chapter 2: Generalized alternating method of Schwarz. Chapter 3: Effective Medium Approximation. Chapter 4: Circular and elliptic inclusions. Section 3: Macroscopic properties of 2D piezoelectric composites. Chapter 5: Fibrous magneto-electro-elastic composites. Section 4: Image analysis and machine learning. Chapter 6: Digital Image Processing and basic granulometry. Chapter 7: Cancer cells detection using Neural Networks. Chapter 8: Applications. Appendix A: Elliptic functions. References. Index.