One dimensional convolutions
A convolution of an one-dimensional array with a kernel comprises of taking the kernel, sliding it along the array, multiplying it with the items in the array that overlap with the kernel in that location and summing this product.
Bu egzersiz
Image Modeling with Keras
kursunun bir parçasıdırEgzersiz talimatları
Multiply each window in the input array with the kernel and sum the multiplied result and allocate the result into the correct entry in the output array (conv).
Uygulamalı interaktif egzersiz
Bu örnek kodu tamamlayarak bu egzersizi bitirin.
array = np.array([1, 0, 1, 0, 1, 0, 1, 0, 1, 0])
kernel = np.array([1, -1, 0])
conv = np.array([0, 0, 0, 0, 0, 0, 0, 0, 0, 0])
# Output array
for ii in range(8):
conv[ii] = (____ * array[____:____+____]).sum()
# Print conv
print(conv)