Concurrent learning and performance information processing system

A computer processing system for updating a matrix of elements for use in determining the relationship among a plurality of variables, comprising:

• a plurality of processors, each of said processors operative to receive an input variable of a plurality of input variables in parallel received during a time trial;
• an ordered array of memory elements associated with each processor, each of said memory elements defining elements of a matrix, each of said memory elements containing values that are operative to define a relationship among received input variables and each of said memory elements operative to be updated by each of said processors;
• each of said processors operative to be uniquely paired with every other processor of said computer system;
• said uniquely paired processors sharing data via a memory element associated with each unique pair of processors;
• and
• each of said processors updating said memory elements to reflect the relationship among input variables received during a time trial.

A computer processing system for computing a matrix of elements, comprising:

• a plurality of processing units, each of said processing units operative to receive, during a time trial and in parallel, individual input values from an input vector e[IN];
• an ordered array of memory elements associated with each processor, each of said memory elements defining elements of a symmetric matrix ω;
• each of said processors operative to be uniquely paired with every other processor of said computer system, thereby forming a processor pair ƒ and g;
• said uniquely paired processors sharing data via a memory element uniquely associated with each unique pair of processors;
• and
• each of said processors computing said memory elements during a time trial by multiplying said input vector e[IN] by said symmetric matrix ω.

A computer processing system for modifying the elements ω{ƒ,ƒ} of a connection weight matrix used to produce an output based on inputs received during a time trial, comprising:

• a plurality of processing units, each of said processing units operative to receive, during a time trial and in parallel, individual input variables from an input vector ω<ƒ>;
• an ordered array of memory elements associated with each processor, each of said memory elements defining elements of a matrix ω<ƒ,ƒ>, each of said memory elements containing values that are operative to define a relationship among received input variables and each of said memory elements operative to be modified by each of said processors;
• each of said processors operative to be uniquely paired with every other processor of said computer system;
• said uniquely paired processors sharing data via a memory element uniquely associated with each unique pair of processors;
• and
• each of said processors updating said memory elements to reflect the relationship among input variables received during a time trial.

A computer processing system for updating a matrix of elements for use in determining the relationship among a plurality of variables, comprising:

• a plurality of processors, each of said processing units operative to receive, during a time trial and in parallel, individual input values from an input vector m[IN];
• a plurality of interconnected conductors, operative to connect each of said processing units to every other processing unit of said system and operative to transfer weighted values among said processors;
• a variance-covariance matrix of elements ν associated with a processor, each of said memory elements being variance-covariance matrix values ν defining elements of a matrix, each of said memory elements containing values that are operative to define a relationship among received input variables and each of said memory elements operative to be updated, by each of said processors, according to the equation:
• ν[OUT]=lm[IN]Tm[IN]+ν[IN]/(1+l),
• where l is a learning weight;
• and
• wherein said matrix of elements is inverted for use in providing output values from said input values.

A method for updating a matrix of elements for use in determining the relationship among a plurality of variables in a computer processing system, comprising:

• receiving individual input values from an input vector m[IN];
• and
• updating a variance-covariance matrix of elements ν associated with a processor according to the equation:
• ν[OUT]=lm[IN]Tm[IN]+ν[IN]/(1+l),
• where l is a learning weight,
• said elements being variance-covariance values ν defining elements of a variance-covariance matrix ν, each of said elements containing values that are operative to define the relationship among received input variables.

A processing system for computing output values from input values received during a series of time trials, comprising:

• a processing unit operative to receive an input vector comprising a plurality of input data values for each time trial;
• a memory unit, connected to the processing unit, containing elements defining a connection weight matrix that is the inverse of a covariance matrix based on regression analysis applied to input data values received during prior time trials;
• said processing unit operative to provide, during each time trial, one or more output values calculated as a function of the input data values for the time trial and the elements of the connection weight matrix;
• and
• said processing unit operative to update the elements of the connection weight matrix, during each time trial, based on covariance relationships among the input values received during the time trial.