A matrix-product (tensor-train-like) representation of Boolean functions, built from row-switching matrices, is proven to be a canonical normal form equivalent to quasi-reduced binary decision diagrams.
These methods are implemented on given BMPs via the SWAP operation, which changes the order of two adjacent variables in the matrix train
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A Matrix Product State Representation of Boolean Functions
A matrix-product (tensor-train-like) representation of Boolean functions, built from row-switching matrices, is proven to be a canonical normal form equivalent to quasi-reduced binary decision diagrams.