Is it possible to predict the design based on the desired output goals? Already, some evolutionary antenna design techniques are present but how can we apply machine learning?
Generally, the process of antenna design requires to find out the EM characteristics of antenna by observing the current distributions through simulations. These EM properties are then used for the parameters optimization. Machine learning (ML) can be combined with simulations to design an antenna. In smart antenna array, the reconfiguration of antenna can be obtained by optimization using Machine learning and Support Vector Machines (SVM). SVMs are a good candidate for the solution of antenna array processing problems such as beamforming and the angle of arrival estimation, because these algorithms provide superior performance in generalization ability and computational complexity.
Machine learning based methods are used for calculating the radar cross section (RCS) of the antenna-radome system. In this method, the back-propagation algorithm can be used to train the machine learning model. The machine leaning based RCS calculation becomes a promising area, especially for the industrial sector with large amount of measurement data. Compared to traditional methods, machine learning methods have the potential to handle complex.
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Machine Learning Modems: How ML will change how we specify and ...
https://www.comsoc.org/.../machine-learning-modems-how-ml-will... - Traduire cette pageMachine Learning Modems: How ML will change how we specify and design next ... Tim point us towards a fascinating new way to specify and design communication ... Dr. Tim O'Shea, CTO at DeepSig Inc. & Research Scientist at Virginia Tech ... As algorithm complexity, number of devices, number of antennas, number of ...
How can we use machine learning for designing antenna?
https://www.researchgate.net/.../How_can_we_use_machine_learni... - Traduire cette pageRead 3 answers by scientists with 3 recommendations from their colleagues to the question asked by Kanhaiya Sharma on Jan 10, 2018.
I suggest to have a look to this article, hope you find it useful.
An Efficient Method for Antenna Design Optimization Based on Evolutionary Computation and Machine Learning Techniques, IEEE Transactions on Antennas and Propagation 62(1):7-18, January 2014. DOI: 10.1109/TAP.2013.2283605
Generally, the process of antenna design requires to find out the EM characteristics of antenna by observing the current distributions through simulations. These EM properties are then used for the parameters optimization. Machine learning (ML) can be combined with simulations to design an antenna. In smart antenna array, the reconfiguration of antenna can be obtained by optimization using Machine learning and Support Vector Machines (SVM). SVMs are a good candidate for the solution of antenna array processing problems such as beamforming and the angle of arrival estimation, because these algorithms provide superior performance in generalization ability and computational complexity.
Machine learning based methods are used for calculating the radar cross section (RCS) of the antenna-radome system. In this method, the back-propagation algorithm can be used to train the machine learning model. The machine leaning based RCS calculation becomes a promising area, especially for the industrial sector with large amount of measurement data. Compared to traditional methods, machine learning methods have the potential to handle complex.
I suggest to have a look to this article, hope you find it useful:
Direction of arrival estimation for smart antenna in multipath environment using convolutional neural network (Y. Harkouss et al.)
Article Direction of arrival estimation for smart antenna in multipa...
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