Patent ID: 7352918

Claim:
A method for learning a small block pattern and a large block pattern related thereto having a different number of components than the small block pattern, the method comprising: a) providing a small block pattern and a large block pattern related thereto; b) applying said small block and large block patterns to a dedicated processor for computing coefficients of a transform function that will subsequently allow determination of estimated values for a selected small block pattern in a recognition phase, these coefficients being components of an intermediate pattern; c) storing the small block pattern in an artificial neural network composed of neurons capable of storing the small block pattern or data related thereto as a prototype with a category associated with each prototype; d) storing said intermediate pattern in a memory at a location that can be addressed by said category, said category acting as a pointer to said intermediate pattern; and e) wherein upon receipt of the selected small block pattern, a closest prototype stored by the artificial neural network is identified and the associated category is extracted to act as a pointer to the stored intermediate pattern, wherein an up-converted image is generated by applying the retrieved intermediate pattern to the received, selected small block pattern.