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About Nonlinear Optimization Lecture 1: Introduction: Professor Frank E. Curtis
This document is the introduction to a lecture on nonlinear optimization. It provides examples of nonlinear optimization problems in data fitting, optics, and robotics. It then discusses how nonlinear problems are more difficult to solve than linear problems. The lecture will cover topics like characterizing optimal solutions, modern optimization algorithms, and the theoretical convergence of algorithms. It focuses on finite-dimensional, deterministic, smooth, and continuous optimization problems.
Detailed Information
| Author: | ['bill'] |
|---|---|
| Publication Year: | 2016 |
| Pages: | 24 |
| Language: | English |
| Format: | |
| Price: | FREE |
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