Classifying system having a single neural network architecture for multiple input representations

A method for classifying input characters, comprising the steps of:

• developing a plurality of non-scalar representations of a character to be classified, and at least one scalar representation of said character defining a character recognition feature which is capable of distinguishing different characters from one another;
• separately processing said non-scalar representations in respective classification channels of a neural network, each of which has at least one hidden layer of processing nodes, to produce intermediate values indicative of an input character;
• coupling values related to said scalar representation to the hidden layer of said classification channels;
• and
• processing the intermediate values from said classification channels in an output layer of processing nodes of said neural network, to produce output values representative of the probable classification of the input character.

A classification system for classifying input characters, comprising:

• an input device which develops a plurality of representations of a character to be classified, wherein each of said representations defines a character recognition feature which is capable of distinguishing different characters from one another;
• and
• a neural network having:
• a plurality of primary classification channels each having at least one hidden layer of processing nodes, each of said primary classification channels processing a different one of said representations to produce intermediate values indicative of an input character;
• an output layer of processing nodes which receives the intermediate values from said plurality of primary classification channels to produce output values representative of the probable classification of an input character;
• and
• a secondary classification channel having at least one input node which receives another one of said representations of said character and produces output values that are coupled to said hidden layers of said primary classification channels.

A classification system for classifying input characters, comprising:

• an input device which develops a plurality of representations of a character to be classified, including at least one scalar representation of said character;
• and
• a neural network having:
• a plurality of primary classification channels each having at least one hidden layer of processing nodes, each of said primary classification channels processing a respective one of said representations to produce intermediate values indicative of an input character;
• an output layer of processing nodes which receives the intermediate values from said plurality of primary classification channels to produce output values representative of the probable classification of an input character;
• and
• a secondary classification channel having at least one input node which receives said scalar representation and produces output values that are coupled to said hidden layers of said primary classification channels and are also directly coupled to said output layer of said neural network.

A method for classifying input characters, comprising the steps of:

• developing a plurality of representations of a character to be classified, including at least one scalar representation of said character;
• separately processing said representations in respective classification channels of a neural network, each of which has at least one hidden layer of processing nodes, to produce intermediate values indicative of an input character;
• coupling values related to said scalar representation to the hidden layer of each of said classification channels;
• processing the intermediate values from said classification channels in an output layer of processing nodes of said neural network, to produce output values representative of the probable classification of the input character;
• and
• directly coupling the values related to said scalar representation to said output layer of said neural network in addition to coupling them to said hidden layer.

A classification system for classifying input characters, comprising:

• an input device which develops a plurality of representations of a character to be classified;
• and
• a neural network having:
• a plurality of primary classification channels each having at least one hidden layer of processing nodes, each of said primary classification channels processing a different one of said representations to produce intermediate values indicative of an input character;
• an output layer of processing nodes which receives the intermediate values from said plurality of primary classification channels to produce output values representative of the probable classification of an input character;
• and
• a secondary classification channel having at least one input node which receives another one of said representations of said character and produces output values that are coupled to said hidden layers of said primary classification channels and are also directly coupled to said output layer of said neural network.