# adobe-research/MetaAF

<https://repo.masters-masters.com/en/repos/adobe-research/MetaAF>

[Home](https://repo.masters-masters.com/en) › [adobe-research](https://repo.masters-masters.com/en/owners/adobe-research) › [MetaAF](https://repo.masters-masters.com/en/repos/adobe-research/MetaAF)

adobe-research/MetaAF has 274 stars on GitHub. Its RepoMasters card: Alpha tier. Control adaptive filters with neural networks. Language: Python.

| Field | Value |
| --- | --- |
| Owner | [adobe-research](https://repo.masters-masters.com/en/owners/adobe-research) |
| Stars | 274 |
| Forks | 45 |
| Language | [Python](https://repo.masters-masters.com/en/languages/python) |
| License | None |
| Created | 2022 |
| Topics | beamforming, acoustic-echo-cancellation, adaptive-filtering, adaptive-filters, dereverberation, gsc, linear-prediction, system-identification, blind-equalization, weighted-prediction-error |
| Tier | [Alpha (250 to 699 ★)](https://repo.masters-masters.com/en/ranks/b_movie) |
| View on GitHub | [adobe-research/MetaAF](https://github.com/adobe-research/MetaAF) |

## Repository

Control adaptive filters with neural networks.

The tier for repos with 250 to 699 ★. Published odds per card pulled: 20%. Rarity: Uncommon.

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Data: GitHub · Illustration drawn by RepoMasters from the repo’s ID and its language color.