Debasish Roy & G. Visweswara Rao
Derivative-based Methods of Optimization; Riemannian Differential Geometry; Direct Search Methods of Optimization; Geometrically Inspired Stochastic Filtering and Optimization; Geometrically Inspired Markov Chain Monte Carlo (MCMC); Penalty Function Methods Electrical This comprehensive textbook covers both classical and geometric aspects of optimization using methods aerospace and communication engineering.This textbook comprehensively treats both classical and geometric optimization methods and stochastic dynamics on manifolds. The textbook is accompanied by online resources including MATLAB codes which are uploaded on our website. The textbook is primarily written for senior undergraduate and graduate students in all applied science and engineering disciplines and can be used as a main or supplementary text for courses on classical and geometric optimization.The book includes: deterministic and stochastic electronics evolutionary methods geometric search using Riemannian Langevin dynamics in a single volume and in a language accessible to non-mathematicians. It will serve as an ideal study material for senior undergraduate and graduate students in the fields of civil including deterministic and stochastic (Monte Carlo) schemes. It provides extensive coverage of important topics including derivative-based methods mechanical method of gradient projection penalty function methods
Publisher: CRC Press
Published: Dec 15, 2024
Description:
This comprehensive textbook covers both classical and geometric aspects of optimization using methods, deterministic and stochastic, in a single volume and in a language accessible to non-mathematicians. It will serve as an ideal study material for senior undergraduate and graduate students in the fields of civil, mechanical, aerospace, electrical, electronics, and communication engineering.This textbook comprehensively treats both classical and geometric optimization methods, including deterministic and stochastic (Monte Carlo) schemes. It provides extensive coverage of important topics including derivative-based methods, penalty function methods, method of gradient projection, evolutionary methods, geometric search using Riemannian Langevin dynamics, and stochastic dynamics on manifolds. The textbook is accompanied by online resources including MATLAB codes which are uploaded on our website. The textbook is primarily written for senior undergraduate and graduate students in all applied science and engineering disciplines and can be used as a main or supplementary text for courses on classical and geometric optimization.The book includes: Derivative-based Methods of Optimization.Direct Search Methods of Optimization.Basics of Riemannian Differential Geometry.Geometric Methods of Optimization using Riemannian Langevin Dynamics.Stochastic Analysis on Manifolds and Geometric Optimization Methods.