问题描述:

Recently I'm learning BP Neural Network for my English letter recognition. I implement a simple edition and find somthing confusing.

My simple edition is to recognize whether the input binary image is a u.

I have a binary image of a letter and extract the feature vector of that image by counting the foreground pixels of every 3x3 block. For example, for a 24x24 image, the size of feature vector is 64.

Output 1 for is a u and 0 for isn't a u.

Then there's what I'm confused about:

First I input a u for training. and input u, c, p, b, d one by one to test. I get 5 1s.

Then I input u, c, p, b, d one by one for training, and input u, c, p, b, d one by one to test. I get 5 0s

Is it that the result of new training changes the result of old training makes the recognition fail?

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