IRMA-International.org: Creator of Knowledge
Information Resources Management Association
Advancing the Concepts & Practices of Information Resources Management in Modern Organizations

Electromagnetic Optimization using Genetic Algorithms

Electromagnetic Optimization using Genetic Algorithms
View Sample PDF
Author(s): P. Mukherjee (Institute of Engineering & Management, India)and E. L. Hines (University of Warwick, UK)
Copyright: 2010
Pages: 13
Source title: Soft Computing Methods for Practical Environment Solutions: Techniques and Studies
Source Author(s)/Editor(s): Marcos Gestal Pose (University of A Coruna, Spain)and Daniel Rivero Cebrián (University of A Coruna, Spain)
DOI: 10.4018/978-1-61520-893-7.ch007

Purchase

View Electromagnetic Optimization using Genetic Algorithms on the publisher's website for pricing and purchasing information.

Abstract

This chapter focuses on the application of Genetic Algorithms (GAs) techniques in overcoming the limitations of microstrip antennas in terms of several key parameters such as bandwidth, power-handling capacity etc. In this chapter the effectiveness of GAs is discussed in relation to Electromagnetic optimization. A matching network has been designed for single band and dual band matching of microstrip antenna using GA.

Related Content

Bhargav Naidu Matcha, Sivakumar Sivanesan, K. C. Ng, Se Yong Eh Noum, Aman Sharma. © 2023. 60 pages.
Lavanya Sendhilvel, Kush Diwakar Desai, Simran Adake, Rachit Bisaria, Hemang Ghanshyambhai Vekariya. © 2023. 15 pages.
Jayanthi Ganapathy, Purushothaman R., Ramya M., Joselyn Diana C.. © 2023. 14 pages.
Prince Rajak, Anjali Sagar Jangde, Govind P. Gupta. © 2023. 14 pages.
Mustafa Eren Akpınar. © 2023. 9 pages.
Sreekantha Desai Karanam, Krithin M., R. V. Kulkarni. © 2023. 34 pages.
Omprakash Nayak, Tejaswini Pallapothala, Govind P. Gupta. © 2023. 19 pages.
Body Bottom