Design and Implementation of CPW-Fed Microstrip Patch Antenna, Synthesis and Analysis using MLP and Machine Learning for Wireless Applications

In this project a CPW-fed frequency Reconfigurable Microstrip antenna, which can be smoothly tuned over a wide range of frequencies of 2.5GHz to 10.8 GHz is proposed. This model uses FR4 Epoxy as a substrate with thickness of 1.6mm with a dielectric loss tangent of 0.02. This antenna can be used for different applications such as Weather Radar, Mobile Communication, WLAN, Long distance Radio and Telecommunications etc., Dataset is created by using the obtained results in HFSS. Antenna analysis and synthesis is carried out using Multi-Layer Perceptron and Linear Regression using Machine Learning and SPSS software. Back propagation algorithm is used to train the neural network to obtain minimum squared error.