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I am trying to implement CNN using tensorflow on temporal accelrometer signal.

  • I have signal values segmented on every 10ms (200 samples).
  • I want to perform 1-D convolution (tf.nn.conv1d(x,W,stride=1,padding='VALID'))
  • Convolution window size is 20 samples and stride of 1 with 32 features and Valid padding
  • I want to apply Max-Pooling with window size of 10 samples tf.nn.max_pool(x,ksize=[1,1,10,1],strides= [1,1,2,1],padding='VALID')

But i am getting errors regarding dimensions of tensors. Any suggestions on how can i set filter size and stride for booth convolution and max-pooling

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