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This project classifies two groups (walking and running) from the FMCW dataset. Different deep learning models (LSTM, GRU) will be used.

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v24
v24
 
 
v25_simpified
v25_simpified
 
 
v26
v26
 
 
v27
v27
 
 
v30
v30
 
 
v31
v31
 
 
3_Spectrograms_CI4R_Datasets_77GHz_Multi_Class_LSTM.ipynb
3_Spectrograms_CI4R_Datasets_77GHz_Multi_Class_LSTM.ipynb
 
 
3_Spectrograms_CI4R_Datasets_77GHz_Multi_Class_LSTM_with_Attention(steps_divided_4).ipynb
3_Spectrograms_CI4R_Datasets_77GHz_Multi_Class_LSTM_with_Attention(steps_divided_4).ipynb
 
 
3_Spectrograms_CI4R_Datasets_77GHz_Multi_Class_LSTM_with_Attention.ipynb
3_Spectrograms_CI4R_Datasets_77GHz_Multi_Class_LSTM_with_Attention.ipynb
 
 
3_Spectrograms_CI4R_Datasets_77GHz_Multi_Class_only_LSTM_with_Attention.ipynb
3_Spectrograms_CI4R_Datasets_77GHz_Multi_Class_only_LSTM_with_Attention.ipynb
 
 
3_Spectrograms_CI4R_Datasets_Multi_Class_CNN.ipynb
3_Spectrograms_CI4R_Datasets_Multi_Class_CNN.ipynb
 
 
3_Spectrograms_CI4R_Datasets_Multi_Class_LSTM.ipynb
3_Spectrograms_CI4R_Datasets_Multi_Class_LSTM.ipynb
 
 
3_Spectrograms_CI4R_Datasets_Multi_Class_LSTM_with_Attention.ipynb
3_Spectrograms_CI4R_Datasets_Multi_Class_LSTM_with_Attention.ipynb
 
 
3_Spectrograms_CI4R_Datasets_Multi_Class_LSTM_with_Attention_Siamese.ipynb
3_Spectrograms_CI4R_Datasets_Multi_Class_LSTM_with_Attention_Siamese.ipynb
 
 
FMCW_Data_CNN.ipynb
FMCW_Data_CNN.ipynb
 
 
FMCW_GRU.ipynb
FMCW_GRU.ipynb
 
 
FMCW_LSTM_k_fold_validation.ipynb
FMCW_LSTM_k_fold_validation.ipynb
 
 
FMCW_LSTM_k_fold_validation_not_oversampled.ipynb
FMCW_LSTM_k_fold_validation_not_oversampled.ipynb
 
 
FMCW_LSTM_v1.ipynb
FMCW_LSTM_v1.ipynb
 
 
FMCW_LSTM_v2.ipynb
FMCW_LSTM_v2.ipynb
 
 
FMCW_LSTM_v3.ipynb
FMCW_LSTM_v3.ipynb
 
 
README.md
README.md
 
 
Range Doppler LSTM Network.drawio
Range Doppler LSTM Network.drawio
 
 
RangeDopplerLSTMImproved.ipynb
RangeDopplerLSTMImproved.ipynb
 
 
RangeDopplerLSTMUnitNumber32.ipynb
RangeDopplerLSTMUnitNumber32.ipynb
 
 
Range_Doppler_CI4R_Datasets_Multi_Class_CNN_10Ghz.ipynb
Range_Doppler_CI4R_Datasets_Multi_Class_CNN_10Ghz.ipynb
 
 
Range_Doppler_CNN.ipynb
Range_Doppler_CNN.ipynb
 
 
Range_Doppler_LSTM.ipynb
Range_Doppler_LSTM.ipynb
 
 
Range_Doppler_LSTM_Architecture.drawio
Range_Doppler_LSTM_Architecture.drawio
 
 
Range_Doppler_LSTM_v2_32hiddenunit.ipynb
Range_Doppler_LSTM_v2_32hiddenunit.ipynb
 
 
Range_Doppler_LSTM_v2_8hiddenunit.ipynb
Range_Doppler_LSTM_v2_8hiddenunit.ipynb
 
 
Range_Doppler_LSTM_v2_datalarla.ipynb
Range_Doppler_LSTM_v2_datalarla.ipynb
 
 
Range_Doppler_LSTM_v2_datalarla_denseunit128.ipynb
Range_Doppler_LSTM_v2_datalarla_denseunit128.ipynb
 
 
Range_Doppler_LSTM_v2_datalarla_denseunit512.ipynb
Range_Doppler_LSTM_v2_datalarla_denseunit512.ipynb
 
 
Range_Doppler_LSTM_v2_datalarla_dropout01.ipynb
Range_Doppler_LSTM_v2_datalarla_dropout01.ipynb
 
 
Range_Doppler_LSTM_v2_datalarla_dropout03.ipynb
Range_Doppler_LSTM_v2_datalarla_dropout03.ipynb
 
 
Range_Doppler_and_Spectrogram_CNN.ipynb
Range_Doppler_and_Spectrogram_CNN.ipynb
 
 
Range_Doppler_and_Spectrogram_CNN_compare_slow_and_pocket.ipynb
Range_Doppler_and_Spectrogram_CNN_compare_slow_and_pocket.ipynb
 
 
Range_Doppler_and_Spectrogram_Hybrid_CNN_LSTM.ipynb
Range_Doppler_and_Spectrogram_Hybrid_CNN_LSTM.ipynb
 
 
Range_Doppler_and_Spectrogram_LSTM.ipynb
Range_Doppler_and_Spectrogram_LSTM.ipynb
 
 
Range_Doppler_and_Spectrogram_Multi_Class_CNN.ipynb
Range_Doppler_and_Spectrogram_Multi_Class_CNN.ipynb
 
 
Range_Doppler_multi_class_LSTM.ipynb
Range_Doppler_multi_class_LSTM.ipynb
 
 
SignalProcessing_Spectrograms
SignalProcessing_Spectrograms
 
 
SpectrogramOfComplexSignalExample.pdf
SpectrogramOfComplexSignalExample.pdf
 
 
Spectrogram_CI4R_Datasets_Multi_Class_CNN.ipynb
Spectrogram_CI4R_Datasets_Multi_Class_CNN.ipynb
 
 
Spectrogram_CNN.ipynb
Spectrogram_CNN.ipynb
 
 
Spectrogram_LSTM.ipynb
Spectrogram_LSTM.ipynb
 
 
Spectrogram_and_Range_Doppler_LSTM_Architecture.drawio
Spectrogram_and_Range_Doppler_LSTM_Architecture.drawio
 
 
Untitled Diagram.drawio
Untitled Diagram.drawio
 
 
addjitter_to_oversampleddata.m
addjitter_to_oversampleddata.m
 
 
create_spectrograms_realdata.m
create_spectrograms_realdata.m
 
 
createallspectrograms.m
createallspectrograms.m
 
 
extract_features_twoclass.m
extract_features_twoclass.m
 
 
folder2
folder2
 
 
nested_k_fold_gru.ipynb
nested_k_fold_gru.ipynb
 
 
oversample_traindata.m
oversample_traindata.m
 
 
preprocess_and_downscale_range_doppler_data.m
preprocess_and_downscale_range_doppler_data.m
 
 
preprocess_and_downscale_spectrogram_data.m
preprocess_and_downscale_spectrogram_data.m
 
 
results_fix_random_Seed.txt
results_fix_random_Seed.txt
 
 
spectrogramexample_new.m
spectrogramexample_new.m
 
 
spectrograms__50dB_jittered.eps
spectrograms__50dB_jittered.eps
 
 
spectrograms_noiseless.eps
spectrograms_noiseless.eps
 
 
test_results
test_results
 
 
viusalize_noisy_Sepctrograms.m
viusalize_noisy_Sepctrograms.m
 
 

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FMCW-Data-Classification-

This project classifies two groups (walking and running) from the FMCW dataset. Different deep learning models (LSTM, GRU) will be used.

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This project classifies two groups (walking and running) from the FMCW dataset. Different deep learning models (LSTM, GRU) will be used.

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