Lucent Technologies Inc.

Bernard Victorri

John Stewart Denker

Yann Andre LeCun

Patrice Y Simard

In order for neural network technology to make useful determinations of the identity of letters and numbers that are processed in real time at a postal service sorting center, it is necessary for the neural network to 'learn' to recognize accurately the many shapes and sizes in which each letter or number are formed on the address surface of the envelope by postal service users. It has been realized that accuracy in the recognition of many letters and numbers is not appreciably sacrificed if the neural network is instructed to identify those characteristics of each letter or number which are in the category 'invariant.' Then, rather than requiring the neural network to recognize all gradations of shape, location, size, etc. of the identified invariant characteristic, a generalized and bounded description of the invariant segments is used which requires far less inputting of sample data and less processing of information relating to an unknown letter or number.

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Paris, France

Bernard Victorri