Skip to content
Database for FMCW THz radars (HR workspace)
Python
Branch: master
Clone or download
labRadioVision Rename federated_withthzdata_sample.py to federated_thzdata_sample.py
Python script example (federated learning with a single layer neural network for testing)
Latest commit 24a6fba Aug 7, 2019

README.md

Readme for mat files (database)

Database for FMCW THz radars (HR workspace) and sample code for federated learning Open with (python code):

import scipy.io as sio database = sio.loadmat('data_base_all_sequences_random.mat')

The database contains 5 files:

  • Data_test_2.mat: dimension 16000 x 512 - x_test = database['Data_test_2'] Contains 16000 FFT range measurements (512-point FFT of beat signal after DC removal) used for test database with corresponding labels in label_test_2.mat

  • Data_train_2.mat: dimension 16000 x 512 - x_train = database['Data_train_2']
    Contains 16000 FFT range measurements (512-point FFT of beat signal after DC removal) used for training database with corresponding labels in lable_train_2.mat

  • label_test_2.mat: dimension 16000 x 1 - y_test = database['label_test_2'] Contains the true labels for test data (Data_test_2.mat), namely classes (true labels) correspond to integers from 0 to 7: Class 0: human worker at safe distance >3.5m from the radar (safe distance) Class 1: human worker at distance (critical) <0.5m from the corresponding radar Class 2: human worker at distance (critical) 0.5m - 1m from the corresponding radar Class 3: human worker at distance (critical) 1m - 1.5m from the corresponding radar Class 4: human worker at distance (safe) 1.5m - 2m from the corresponding radar Class 5: human worker at distance (safe) 2m - 2.5m from the corresponding radar Class 6: human worker at distance (safe) 2.5m - 3m from the corresponding radar Class 7: human worker at distance (safe) 3m - 3.5m from the corresponding radar

  • label_train_2.mat: dimension 16000 x 1 - y_train = database['label_train_2'] Contains the true labels for train data (Data_train_2.mat), namely classes (true labels) correspond to integers from 0 to 7: Class 0: human worker at safe distance >3.5m from the radar (safe distance) Class 1: human worker at distance (critical) <0.5m from the corresponding radar Class 2: human worker at distance (critical) 0.5m - 1m from the corresponding radar Class 3: human worker at distance (critical) 1m - 1.5m from the corresponding radar Class 4: human worker at distance (safe) 1.5m - 2m from the corresponding radar Class 5: human worker at distance (safe) 2m - 2.5m from the corresponding radar Class 6: human worker at distance (safe) 2.5m - 3m from the corresponding radar Class 7: human worker at distance (safe) 3m - 3.5m from the corresponding radar

  • permut.mat (1 x 16000) contains the chosen random permutation for data partition among nodes/device and federated learnig simulation (see python code)

You can’t perform that action at this time.