Applied Iterative Methods

Applied Iterative Methods is a comprehensive textbook on iterative algorithms, combining optimization, convex analysis, and approximation theory, and is widely used in medical imaging, remote sensing, and hyperspectral imaging.

Format: Paperback / softback
Length: 400 pages
Publication date: 30 September 2021
Publisher: Taylor & Francis Ltd

Applied Iterative Methods is a comprehensive and self-contained treatise that serves as an invaluable reference and a textbook suitable for advanced studies in the field of iterative algorithms. It stands as the pioneering work in bringing together diverse subjects such as optimization, convex analysis, and approximation theory, and organizing them around a rigorous and mathematically sound treatment of iterative algorithms. These algorithms find widespread applications in solving complex problems across a wide range of domains, including medical imaging, where they are utilized for tasks such as emission and transmission tomography, magnetic-resonance imaging, and intensity-modulated radiation therapy. Beyond the medical realm, these algorithms find utility in fields like remote sensing and hyperspectral imaging.

Within its pages, Applied Iterative Methods presents a vast array of diverse iterative algorithms that are universally applicable. These algorithms are carefully designed to address a wide range of problems, ranging from optimization and linear algebra to numerical analysis and signal processing. Each algorithm is presented with clear explanations, accompanied by illustrative examples and computational implementations, making it accessible to both experts and beginners in the field.

The book is organized into several chapters, each dedicated to a specific topic or application area. The first chapter provides an introduction to iterative algorithms and their theoretical foundations, while subsequent chapters delve into specific algorithms and their applications. The chapters are further divided into subsections, allowing for a detailed exploration of the algorithms' properties, convergence analysis, and practical considerations.

One of the key strengths of Applied Iterative Methods is its comprehensive coverage of various iterative algorithms. The book includes well-known algorithms such as the Newton-Raphson method, the conjugate gradient method, and the quasi-Newton method, as well as less commonly used algorithms that are specifically tailored for specific problem types. Each algorithm is discussed in detail, including its theoretical background, implementation details, and potential limitations.

Furthermore, Applied Iterative Methods emphasizes the importance of computational efficiency in iterative algorithms. The book provides insights into techniques for optimizing algorithm performance, such as parallelization, vectorization, and sparse matrix techniques. These techniques enable the efficient solution of large-scale problems, making iterative algorithms a valuable tool in many real-world applications.

In conclusion, Applied Iterative Methods is a groundbreaking work that revolutionizes the study of iterative algorithms. It serves as a valuable resource for researchers, practitioners, and students in the fields of optimization, convex analysis, and approximation theory. By combining these diverse subjects and presenting them in a rigorous and accessible manner, the book enables readers to develop a deep understanding of iterative algorithms and their applications in a wide range of domains. Whether you are a seasoned professional or a newcomer to the field, Applied Iterative Methods will undoubtedly enhance your knowledge and skills in this rapidly evolving area.

Weight: 739g
Dimension: 229 x 152 (mm)
ISBN-13: 9780367446161