Effect of Varying the Substrates and Turns of a SR in the Design of Edge Chamfered Microstrip Patch Antenna through Artificial Neural Networks and Meta Resonators
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Abstract
In this paper, the design of size reduced patch antenna for various wireless applications using Artificial Neural Networks (ANN) is presented. Two Network; Cascade forward Back propagation and Feed forward Back Propagation Networks are Simulated, Trained and Tested to yield the optimized design of the Conventional Patch. The conventional patch is designed to resonate at 2.785 GHz with the aid of ANN and an FEM based simulator; while the proposed rectangular patch has triple resonances 1.78, 2.58, 2.87 GHz. The antenna is conveniently modified in to a Heptagon by chamfering one of its edges. Spiral resonator is effectively used in its ground plane to create miniaturization. The Antenna has a gain of 2.368, 2.706, 4.262 dBs respectively.
Keywords: Rectangular microstrip patch antenna (RMPA), Slots, Miniaturisation, Linear Polarization, WLAN, WIMAX, DCS, ANN, FF, CF.
Keywords: Rectangular microstrip patch antenna (RMPA), Slots, Miniaturisation, Linear Polarization, WLAN, WIMAX, DCS, ANN, FF, CF.
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