Convex minimization, a subfield of optimization, studies the problem of minimizing convex functions over convex sets. The convexity property can make optimization in some sense "easier" than the general case - for example, any local minimum must be a global minimum.
Applications:
- automatic control systems
- estimation and signal processing
- communications and networks,
- electronic circuit design
- data analysis and modeling
- statistics
- finance
