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I have an input x (a word), and I have a neural network Y such that Y(x), which is an image always satisfies F(x), and another neural network Z such that Z(x), which is also an image, always satisfies G(x). Is there any way to turn this into a neural network Q where Q(x), which is also a image, satisfies "F(x) ∧ G(x)"?

Thanks!

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No, not in general. It's possible that $G(x)=\neg F(x)$, for instance.

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