Pattern recognition neural network with saccade-like operation

A multi-layered neural network system for pattern recognition, comprising:

• an input field containing a plurality of adjacently disposed objects;
• a scanning mechanism for generating a two-dimensional scan window and scanning said scan window over said objects such that said scan window contains at least two of said adjacent objects;
• an input layer for mapping into said two-dimensional scan window;
• an output layer comprised of at least a first output node with an associated activation energy that is activated to represent the presence of a desired one of said objects substantially centered in said scan window, the activation energy thereof, and a second output node with an associated activation energy that is activated to represent a desired distance from a frame of reference in said scan window to another and adjacent one of said objects when the activation energy is raised above a predetermined threshold;
• a hidden layer having local receptor fields and interconnected with said input layer and said output layer for mapping said input layer to said output layer, said hidden layer providing a representation of this position of the desired object relative to the substantial center of said scan window such that said first output node is activated in response thereto, said hidden layer providing a representation of the desired distance when said adjacent object is separated from said frame of reference in said scan window by substantially said desired distance such that said second output node is activated in response thereto;
• and
• a processor for receiving the output of said first output node and recognizing when the first output node is activated indicating the presence of said desired object centered in said scan window and providing an output in response thereto, and said processor operable to receive said second output node and controlling said scanning mechanism to move by a distance substantially corresponding to said associated desired distance when said second node is activated.

A method for recognizing a pattern, comprising:

• providing an input layer in a neural network;
• mapping the input layer into a two dimensional scan window, the scan window defining an input space that can be scanned over objects, and which scan window can contain at least two adjacent ones of the objects;
• providing an output layer in the neural network having at least a first output node with an associated activation energy that is operable to be activated to represent the presence of a desired one of the objects relative to the substantial center of the scan window and a second output node with an associated activation energy that is activated to represent a desired distance between the frame of reference within the scan window and the one of the objects not substantially centered in the scan window;
• the first and second output nodes activated when the associated activation energies rise above respective predetermined thresholds;
• providing a hidden layer in the neural network and interconnecting the hidden layer with the input layer and the output layer;
• mapping the input layer to the output layer with the hidden layer, the hidden layer providing a representation of the position of the desired one of the objects relative to the substantial center of the scan window, and providing a representation of the desired distance when the desired one of the objects not substantially centered in the scan window is separated from the frame of reference by substantially the desired distance;
• activating the first output node in response to the desired one of the objects being disposed within the scan window and substantially corresponding to the representation in the hidden layer;
• and
• activating the second output node when the distance from the frame of reference to the one of the objects not substantially centered in the scan window is substantially equal to the desired distance.

A method for recognizing a pattern, comprising:

• providing an input layer in a neural network;
• mapping the input layer into the scan window;
• providing an output layer in the neural network having at least a first output node with an associated activation energy that is activated to represent the presence of a desired object in the scan window and the position thereof relative to the substantial center of the scan window and a second output node with an associated activation energy that is activated to represent a desired distance between the frame of reference within the scan window and the one of the objects not substantially centered in the scan window;
• providing a hidden layer in the neural network and interconnecting the hidden layer with the input layer and the output layer;
• mapping the input layer to the output layer with the hidden layer, the hidden layer providing a representation of the position of the desired object relative to the substantial center of the scan window, and providing a representation of the desired distance when the object not substantially centered in the scan window is separated from the frame of reference by substantially the desired distance;
• activating the first output node by raising its associated activation energy to a level representing the position of the desired object relative to the substantial center of the scan window in response to the desired object being disposed in of the scan window and substantially corresponding to the representation in the hidden layer;
• activating the second output node by raising its associated activation energy above a predetermined threshold when the distance from the frame of reference to the one of the objects not substantially centered in the scan window is substantially equal to the desired distance;
• and
• moving the scan window by a distance substantially corresponding to the desired distance associated with the second output node after activation of both the first and second output nodes.