Parallel, multi-unit, adaptive pattern classification system using inter-unit correlations and an intra-unit class separator methodology

Claim 1

In a system for classification and identification of patterns, each pattern being represented by an input signal S, said system comprising at least one classification unit U i including: (1) pattern feature encoding means, responsive to said signal S, for producing an intermediate signal F, comprised of signal components F 1 , F 2 . . . F i . . . F k , representative of features contained in the pattern represented by said signal S; and (2) pattern classification means, responsive to said intermediate signal F, for producing an output signal R i representative of a proposed respective class of said pattern represented by said signal S as identified by the features represented by said intermediate signal F; the improvement wherein said pattern classification means include: (a) generalizer means comprising: (i) memory means for storing a plurality of generalizer prototypes within a multi-dimensional pattern space, each generalizer prototype including, as prototype information stored in said memory means: a vector location in said pattern space; a scalar distance, in a given range between a minimum and maximum value, defining the size of a region of influence about said vector location of said generalizer prototype; and a particular class with which said generalizer prototype is associated; and (ii) means for comparing the vector location of an input pattern, represented by said intermediate signal F, with a plurality of said generalizer prototypes stored in said memory means to determine whether said input pattern location falls within a region of influence of at least one of said generalizer prototypes, and for producing a generalizer output classification response, indicative of the class associated with said at least one generalizer prototype, if said input pattern location falls within the region of influence thereof; (b) separator means comprising: (i) memory means for storing a plurality of separator prototypes within said pattern space, each separator prototype including, as prototype information stored in said memory means: a vector location in said pattern space; a scalar distance defining the size of a region of influence about said vector location of said separator prototype; a particular class with which said separator prototype is associated; the identity of a pair of generalizer prototypes with which said separator prototype is associated; and an index specifying a portion of the signal components F 1 , F 2 . . . . F i . . . F k of the pattern space holding the generalizer prototypes with which said separator prototype is associated; (ii) means for comparing the location of an input pattern, represented by the signal components of said intermediate signal F identified by the respective index of a separator prototype, with at least one of said separator prototypes stored in said memory means to determine whether said input pattern location falls within a region of influence of such separator prototype, and for producing a separator output classification response, indicative the class of said input pattern, if said input pattern location falls within the region of influence of such separator prototype; and (c) polling means, responsive to said generalizer means and said separator means, for producing a classification unit output signal R i , in dependence upon said generalizer and separator output classification responses; thereby to identify patterns which fall within the regions of influence of a plurality of generalizer prototypes.

Claim 12

A method for classification and identification of patterns in a system comprising input means for receiving an input signal F comprised of signal components F 1 , F 2 . . . F i . . . F k representing each input pattern as a location in a multi-dimensional pattern space, memory means for storing information, and computer means connected to said input means and to said memory means, said method comprising the steps of: (a) storing in said memory means a plurality of generalizer prototypes within said multi-dimensional pattern space, each generalizer prototype including, as prototype information stored in said memory means: a vector location in said pattern space; a scalar distance, in a range between minimum and maximum value, defining the size of a region of influence about said vector location of said generalizer prototype; and a particular class with which said generalizer prototype is associated; (b) comparing the location of an input pattern, represented by said input signal F, with a plurality of said generalizer prototypes stored in said memory means to determine whether said input pattern location falls within a region of influence of at least one of said generalizer prototypes; (c) producing a generalizer output classification response, indicative of the class associated with said at least one generalizer prototype, if said input pattern location falls within the region of influence thereof; (d) storing in said memory means a plurality of separator prototypes within said pattern space, each separator prototype including, as prototype information stored in said separator memory means: a vector location in said pattern space; a scalar distance defining the size of a region of influence about said vector location of said separator prototype; a particular class with which said separator prototype is associated; the identity of a pair of generalizer prototypes with which said separator prototype is associated; and an index specifying a portion of the signal components F 1 , F 2 , . . . F i . . . F k of the pattern space holding the generalizer prototypes with which said separator prototype is associated; (e) comparing the location of an input pattern, represented by the signal components of said input signal F identified by the respective index of a separator prototype, with at least one of said separator prototypes stored in said memory means to determine whether said input pattern location falls within a region of influence of such separator prototype; (f) producing a separator output classification response, indicative of the pattern class, if said input pattern location falls within the region of influence such separator prototype; and (g) producing an output signal R i , indicative of the class of the input pattern represented by said input signal F i , in dependence upon said generalizer and separator output classification responses; thereby to identify patterns which fall within the regions of influence of a plurality of generalizer prototypes.

Claim 13

A method for classification and identification of patterns in a system comprising input means for receiving an input signal F comprised of signal components F 1 , F 2 . . . F i . . . F k representing each input pattern as a location in a multi-dimensional pattern space, memory means for storing information, and computer means connected to said input means and to said memory means, said method comprising the steps of: (a) storing in said memory means a plurality of generalizer prototypes within said multi-dimensional pattern space, each generalizer prototype including, as prototype information stored in said memory means: a vector location in said pattern space; a scalar distance, in a range between minimum and maximum value, defining the size of a region of influence about said vector location of said generalizer prototype; and a particular class with which said generalizer prototype is associated; (b) comparing the location of an input pattern, represented by said input signal F, with a plurality of said generalizer prototypes stored in said memory means to determine whether said input pattern location falls within a region of influence of at least one of said generalizer prototypes; (c) producing a generalizer output classification response, indicative of the class associated with said at least one generalizer prototype, if said input pattern location falls within the region of influence thereof; (d) storing in said memory means a plurality of separator prototypes within said pattern space, each separator prototype including, as prototype information stored in said separator memory means: a vector location in said pattern space; a scalar distance defining the size of a region of influence about said vector location of said separator prototype; a particular class with which said separator prototype is associated; the identity of a pair of generalizer prototypes with which said separator prototype is associated; and an index specifying a portion of the signal components F 1 , F 2 , . . . F i . . . F k of the pattern space holding the generalizer prototypes with which said separator prototype is associated; (e) comparing the location of an input pattern, represented by the signal components of said input signal F identified by the respective index of a separator prototype, with at least one of said separator prototypes stored in said memory means to determine whether said input pattern location falls within a region of influence of such separator prototype; (f) producing a separator output classification response, indicative of the pattern class, if said input pattern location falls within the region of influence such separator prototype; and (g) producing an output signal R i , indicative of the class of the input pattern represented by said input signal F i , in dependence upon said generalizer and separator output classification responses; thereby to identify patterns which fall within the regions of influence of a plurality of generalizer prototypes.