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Machine Learning Based Microstrip Antenna Design in Wireless Communications
| Content Provider | Scilit |
|---|---|
| Author | Ray, Ranjana Pal, Moumita Umamaheswari, R. Banerjee, Ishita |
| Copyright Year | 2021 |
| Description | With continual evolution in technology and advancement in processing methodology, there is increasing volumes of data and the need to better ways of storing these data, with machine learning based ways taking centrestage in various fields for their optimal data storage design strategies. Machine learning plays a major role in today's technologies that not only wants to fill a gap in need but also design the product to fill the gap in the most efficient way possible. In antenna design, also, machine learning has an important role to play, where the proposed work optimizes microstrip antenna parameters with machine learning techniques. With benefits of using machine learning in Microstrip Antenna Design compared to conventional design methods, the chapter also looks into machine learning as a subset of Artificial Intelligence that can formulate a statistical relationship for mathematical modeling of datasets. We investigate the implementation and accuracy of a few machine learning techniques where we provide background for these techniques to start with and, then, explain how the techniques can be used to optimize the performance of the antenna. In this chapter, our objective can be obtained by changing the array element by changing the material property of the substrate. The basic idea is to change the magnitude and phase-means-excitation-coefficient of each array element. Even in the absence of analytical modeling, a predictive measurement can be promoted with machine learning techniques with input and output data to be applied as a tool to predict system behavior with mathematical equations. The system parameters can be optimized and approximated to obtain a data set that can create the mathematical model. A training set of data is used to create the model that best fits the system characteristics. Book Name: Machine Learning and IoT for Intelligent Systems and Smart Applications |
| Related Links | https://api.taylorfrancis.com/content/chapters/edit/download?identifierName=doi&identifierValue=10.1201/9781003194415-2&type=chapterpdf |
| Ending Page | 33 |
| Page Count | 11 |
| Starting Page | 23 |
| DOI | 10.1201/9781003194415-2 |
| Language | English |
| Publisher | Informa UK Limited |
| Publisher Date | 2021-10-15 |
| Access Restriction | Open |
| Subject Keyword | Book Name: Machine Learning and Iot for Intelligent Systems and Smart Applications Optimal Evolution Machine Learning Mathematical Modeling Microstrip Antenna Design Behavior |
| Content Type | Text |
| Resource Type | Chapter |
