/Adaptive-Beamforming-Using-Machine-Learning-in-Matlab

Adaptive Beamforming techniques can be enhanced using Machine Learning Algorithms.

Primary LanguageMATLAB

Adaptive-Beamforming-Using-Machine-Learning-in-Matlab-(Simulation-video-link-is-down-below)

Adaptive Beamforming techniques can be enhanced by using Machine Learning Algorithms.

As a basis Least Means Squares algorithm (adaptive) was used to calculate weigths and to develop the dataset.

Three different machine learning agorithms were used, so that users can compare different designs and choose suitable results:

1.Adaptive Gradient algorithm was used to improve LMS and enable the model to learn and adjust the learning rate.

2.Deep Learning algorithm with LSTM and Regression layers were used to predict weights and plot Array factors for different inputs.

3.Artificial Neural Networks algorithm was used with the same dataset as deep learning model.

All of the models were built upon easy to use Graphical User Interface where different predictions and algorithms can be compared and visualized.

Note: Results can be improved with different datasets which are left for future development.

Simulation video link: https://youtu.be/zaapLjpq6TE