Thanks! I’ll try that.
What I meant is:
Suppose I want my network to learn a pattern such as 1101 (and say now the kernel size is 4), and my inputs were such as:
x_1 = 1, 0, 0, 1, 1, 0, 1, 0, 0, 0, 0; y_1 = 1
...
x_k = 0, 1, 0, 1, 0, 0, 1, 0, 0, 1, 0; y_k =  0

My understanding was that, after I achieved a predetermined acceptable level of accuracy, the learned weights would look something like [0.987, 0.99, -0.0008, 0.959]. Is that understanding incorrect?