Accurate design of miniaturized antenna is constrained by the limited wellformulated exact mathematical expressions. Demands for smart devices with features like portability, implantability, and configurability have further placed bigger challenges in front of the antenna design engineers or scientists. As a part of the search for various solutions, many innovative approaches have been proposed by various authors in different literatures. Application of soft computing is also another design approach to accurate design of fractal antenna. Here, the authors have attempted to propose a better solution to miniaturized antenna and its design. A fractal antenna based on circular outer geometry has been proposed as a solution to the search of miniaturized antennas, and a particle swarm optimization-based selective artificial neural networks ensemble is developed, which is employed as the objective function of a bacterial foraging optimization algorithm leading to a hybridized algorithm. The developed hybrid algorithm is utilized to develop the proposed antenna at 2.45 GHz. A good agreement of the simulated, desired, and experimental results validates the proposed design approach.KEYWORDS ANN ensemble, BFO, fractal antenna, ISM band, PSO | INTRODUCTIONFractal geometry is employed by many researchers to design the miniaturized antennas suitable for compact handheld wireless devices, MIMO applications, rectennas, and implantable devices. 1-5 The requirement for smart and intelligent systems made it imperative to look forward to design methods capable of high precision antenna and antenna systems. The system integration approach further demands for miniaturization of antenna with enhanced parameter capability to meet the demands of bandwidth, gain, directivity, pattern shape, front to back lobe ratio, main to side lobe ratio, noise rejection, and many others. In the present context, fractal antenna due to its properties like self-similar design to maximize the electrical length appears to be a candid choice. The fractal geometry has often features like fine structure at arbitrarily small scale, too irregular to be easily described in Euclidean geometry, self-similar, and has a Hausdorff dimension that is greater than the topological dimension which leads to space filling curves such as Hilbert curve, has a simple and recursive definition, etc; therefore, in the last few years, many researchers are working on fractal antenna to provide many innovative solution.Complex fractal shapes are used for the design of fractal patch antennas. Due to nonexistence of the closed-form exact mathematical formulas for fractal antennas, the design and analysis of these antennas are a challenging task. The analytical methods are suitable for simple microstrip antennas, but derivation of analytical methods is very difficult for fractal

The experimental study of electromagnetic interference of mobile phone radiations on brain waves is a contemporary research area and the ever-increasing use of mobile phones make it more imperative to explore the problem area in detail. Electromagnetic signal from mobile phones operating in Global System for Mobile (GSM) and wide band code division multiple access (WCDMA), has been considered in this paper and their interference impacts have been analyzed on the human electroencephalogram (EEG). The impact on brain waves i.e., delta, theta, alpha, beta and gamma waves are analyzed in five modes namely ideal mode i.e., when mobile phone is not in use, transmission mode and the receiving modes of second generation (2G) and third generation (3G) networks. The data has been acquired from 75 young and healthy students of a post graduate institute while the students were making their routine calls. The acquired EEG signal is analyzed using various parameters viz.; Approximate Entropy(ApEn), Largest Lyapunov Exponent (LLE), Hurst Exponent (HE), Correlation dimension (CD) and the power of the brain waves have also been analyzed. It has been found that due to mobile phone usage, there is variation in the nonlinear parameters and increase in the power of the alpha brain waves at T5O1 during 3GRx and decrease in alpha power at the P4O2 channel in all modes. It has been observed that the change at the right temporal region is more, the side to which mobile phone was held. The Statistical analysis has also been done using SPSS software which shows significant variations at some of the channels in different modes.

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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.