Fractal Antenna Design Using Bio-Inspired Computing Algorithms / Balwinder S. Dhaliwal, Suman Pattnaik, and Shyam Sundar Pattnaik.

Format:

Book

Author/Creator:

Dhaliwal, Balwinder S., author.

Pattnaik, Suman, author.

Pattnaik, Shyam Sundar, author.

Language:

English

Subjects (All):

Antennas (Electronics).

Fractals.

Physical Description:

1 online resource (155 pages)

Edition:

First edition.

Place of Publication:

Singapore : Bentham Science Publishers Pte. Ltd., 2023.

Summary:

This book presents research focused on the design of fractal antennas using bio-inspired computing techniques. The authors present designs for fractal antennas having desirable features like size reduction characteristics, enhanced gain, and improved bandwidths. The research is summarized in six chapters which highlight the important issues related to fractal antenna design and the mentioned computing techniques. Chapters demonstrate several applied concepts and techniques used in the process such as Artificial Neural Networks (ANNs), Genetic Algorithms (GAs), Particle Swarm Optimization (PSO) and Bacterial Foraging Optimization (BFO). The work aims to provide cost-effective and efficient solutions to the demand for compact antennas due to the increasing demand for reduced sizes of components in modern wireless communication devices. A key feature of the book includes an extensive literature survey to understand the concept of fractal antennas, their features, and design approaches. Another key feature is the systematic approach to antenna design. The book explains how the IE3D software is used to simulate various fractal antennas, and how the results can be used to select a design. This is followed by ANN model development and testing for optimization, and an exploration of ANN ensemble models for the design of fractal antennas. The bio-inspired computing techniques based on GA, PSO, and BFO are developed to find the optimal design of the proposed fractal antennas for the desired applications. The performance comparison of the given computing techniques is also explained to demonstrate how to select the best algorithm for a given bio-inspired design. Finally, the book explains how to evaluate antenna designs. This book is a valuable resource for students (from UG to PG levels) and research scholars undertaking learning modules or projects on

microstrip and patch antenna design in communications or electronics engineering courses.

Contents:

Cover

Title

Copyright

End User License Agreement

Contents

Foreword

Preface

Acknowledgements

Recent Advances in The Design and Analysis of Fractal Antennas

INTRODUCTION

ANTENNAS FOR COMMUNICATION APPLICATIONS

ANTENNAS FOR MEDICAL APPLICATIONS

LIMITATIONS OF EXISTING ANTENNA SYSTEMS

FRACTAL ANTENNAS

DESIGN AND ANALYSIS OF FRACTAL ANTENNAS: RECENT DEVE- LOPMENT

CONCLUSION

REFERENCES

Bio-inspired Computing Techniques and their Applications in Antennas

BIO-INSPIRED COMPUTING TECHNIQUES

Artificial Neural Network (ANN)

Multi-Layer Perceptron Neural Networks (MLPNN)

Radial Basis Function Neural Networks (RBFNN)

General Regression Neural Networks (GRNN)

ANN Ensemble

Genetic Algorithm (GA)

Particle Swarm Optimization (PSO) Algorithm

Bacterial Foraging Optimization (BFO) Algorithm

HYBRID BIO-INSPIRED COMPUTING TECHNIQUES

BIO-INSPIRED COMPUTING TECHNIQUES IN ANTENNAS Generated by AI.

Notes:

Description based on publisher supplied metadata and other sources.

Part of the metadata in this record was created by AI, based on the text of the resource.

Description based on print version record.

Includes bibliographical references.

ISBN:

9789815136357

9815136356

OCLC:

1390920773