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// D: number of Doppler bins, 100 in our case | |
// R: number of Range bins, 128 in our case | |
// Det\matrix is the range doppler map | |
// Doppler is the 1D doppler vector | |
int D=100, R=128; | |
float Doppler [D]; | |
// iterate over the doppler bins, and then over the range bins | |
for (int i=0; i < D; i++){ |
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#Handwritten numbers classification | |
import tensorflow as tf | |
from tensorflow import keras | |
from keras.callbacks import EarlyStopping | |
import numpy as np | |
import matplotlib.pyplot as plt | |
tf.executing_eagerly() | |
(x_train, y_train), (x_test, y_test) = keras.datasets.mnist.load_data() |
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#Handwritten numbers classification | |
import tensorflow as tf | |
from tensorflow import keras | |
from keras.callbacks import EarlyStopping | |
import numpy as np | |
import matplotlib.pyplot as plt | |
tf.executing_eagerly() | |
(x_train, y_train), (x_test, y_test) = keras.datasets.mnist.load_data() |