Abstract
In this paper, a mathematical model based on artificial neural network (ANN) is used to design, fabricate and measure a quad-channel microstrip multiplexer. Multi-layer perceptron (MLP) neural network trained with back-propagation algorithm is adopted to model a new microstrip bandpass filter (BPF) based on a novel stub-loaded open-loop resonator. Then, a design process is proposed to obtain four BPFs. Finally, using the obtained BPFs a high-performance microstrip multiplexer is designed. The designed multiplexer has the smallest size and the best insertion and return losses in comparison with the previous multiplexers. It operates at 2.2 GHz, 2.8 GHz, 3.5 GHz and 4 GHz, which are appropriate for multi-band RF wireless communications systems. To validate the ANN model and the simulation results, the proposed quad-channel microstrip multiplexer is fabricated and measured where a good agreement is achieved.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callMore From: AEU - International Journal of Electronics and Communications
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
