| --- |
| language: |
| - en |
| tags: |
| - parameter estimation |
| - wireless channel |
|
|
| --- |
| |
| # deepest |
| `deepest` is a neural network trained to perform wireless channel parameter estimation. |
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| For more information, please refer to the current paper at [Arxiv.org](https://arxiv.org/abs/2211.04846) |
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| A demo with the model can be found in the EMS [Huggingface space](https://huggingface.co/spaces/EMS-TU-Ilmenau/deepest-demo). |
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| If you find it useful and use it in your work, please cite |
| ```text |
| @misc{deepest2022, |
| doi = {10.48550/ARXIV.2211.04846}, |
| url = {https://arxiv.org/abs/2211.04846}, |
| author = {Schieler, Steffen and Semper, Sebastian and Faramarzahangari, Reza and Döbereiner, Michael and Schneider, Christian}, |
| title = {Grid-free Harmonic Retrieval and Model Order Selection using Deep Convolutional Neural Networks}, |
| publisher = {arXiv}, |
| year = {2022}, |
| } |
| ``` |
