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Real and Convex Analysis [Çınlar] - mklabgr - 09-03-2026
Real and Convex Analysis
Authors: Erhan Çınlar, Robert J. Vanderbei
Publication date: January 2013
Publisher: Springer New York
Real and Convex Analysis is a compact introduction to modern mathematical analysis aimed primarily at advanced undergraduate students, graduate students, scientists, and engineers. Rather than developing real analysis only on $\mathbb{R}$, the authors organize the subject around metric spaces, allowing fundamental ideas to be presented in a more general and unified framework. The early chapters establish the basic language of sets, functions, and metric spaces and then develop what the authors describe as the central “four C’s” of analysis: convergence, completeness, compactness, and continuity.
The book then demonstrates how these abstract ideas lead naturally to important applications. It introduces differential and integral equations, followed by convexity and convex optimization, where geometric properties of convex sets and functions form the foundation of optimization theory. The final substantial section introduces measure and integration, providing the basic ideas needed for more advanced probability, functional analysis, and modern integration theory. In this sense, the book connects classical real analysis with subjects of particular importance in applied mathematics, operations research, optimization, engineering, and probability.
A major strength of the book is its economy: at only about 160 pages, it is not intended to replace a comprehensive real-analysis textbook such as Rudin or Royden. Instead, it provides a relatively fast route through the essential concepts while showing how analysis supports modern areas such as convex optimization and probability theory. The chapters progress from Sets and Functions and Metric Spaces through Functions on Metric Spaces, Differential and Integral Equations, Convexity, Convex Optimization, and finally Measure and Integration.
Key takeaways
- Analysis is developed primarily through the framework of metric spaces, rather than only through real-variable calculus.
- The core theoretical ideas are convergence, completeness, compactness, and continuity.
- The book creates an unusually direct bridge between real analysis and convex optimization.
- It also provides introductory treatments of differential equations and measure theory/Lebesgue-style integration.
- It is particularly suitable as a concise transition from undergraduate calculus to more advanced analysis, optimization, probability, or applied mathematics.
BOOK