£107.98

Springer - Introduction to Nonsmooth Optimization Book

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Description

Master the fundamentals of nonsmooth optimization with this comprehensive guide from Springer. As the first easy-to-read text on the subject, this book provides a clear path for understanding nonsmooth optimization (NSO) and its applications in real-world modeling systems. Whether you are working in image denoising, neural network training, or data mining, this text offers the foundational knowledge required to solve complex problems that are not necessarily differentiable. This resource bridges the gap between theoretical concepts and practical implementation. It covers both the mathematical theory and the numerical methods used in NSO, offering a wide overview of the different problems found in the field. The content is organized into three logical parts, starting with convex and nonconvex analysis. This structured approach makes it an essential tool for professionals and students involved in economics, computational chemistry, physics, and optimal control applications.

Key Features

Provides an easy-to-read introduction to nonsmooth optimization (NSO) for those seeking a clear entry point into the subject.

Covers both theoretical foundations and the numerical methods necessary for practical problem-solving in the field.

Addresses real-world applications including image denoising, neural network training, data mining, and optimal control.

Explores diverse industrial uses such as economics, computational chemistry, physics, and various modeling systems.

Organized into a three-part structure that includes comprehensive coverage of convex and nonconvex analysis.

Product Specifications

Format
paperback
Domain
Amazon UK
Release Date
23 August 2016
Listed Since
21 July 2016

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No barcode data available

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