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BeamformNet
BeamformNet:Deep Learning-Based Beamforming Method for DoA Estimation via Implicit Spatial Signal Focusing and Noise Suppression
The DeepSFNS project file is the official implementation of BeamformNet. Among them, deepSFNS. py is the BeamformNet model file.
Firstly, install the environment according to requirements.txt.
Then run the run.py file by python -u ./run.py --root_path ./DeepSFNS --gen_data_config_path ./dataset/gen_data_config.yaml --train_config_path ./train_config.yaml --model_config_path ./models/deepSFNS_config.yaml --validate_config_path ./validate_config.yaml
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DeepSFNS/models/deepSSE.py44 symbols
DeepSFNS/utils/util.py12 symbols
DeepSFNS/models/subspaceNet.py12 symbols
DeepSFNS/utils/dataset.py10 symbols
DeepSFNS/models/daMUSIC.py10 symbols
DeepSFNS/models/deepSFNS.py8 symbols
DeepSFNS/models/IQResNet.py8 symbols
DeepSFNS/utils/loss.py6 symbols
DeepSFNS/dataset/gen_data.py6 symbols
DeepSFNS/utils/metrics.py5 symbols
DeepSFNS/models/source_num_estimator.py5 symbols
DeepSFNS/models/lowSNRNet.py5 symbols
For agents
$ claude mcp add BeamformNet \
-- python -m otcore.mcp_server <graph>