Multi-kernel neural network concurrent learning, monitoring, and forecasting system

This invention relates to neural network information processing systems and, more particularly, relates to a multi-kernel neural network computing architecture configured to learn correlations among feature values as the network monitors and imputes measured input values and also predicts future output values. A multi-kernel neural network computing architecture configured to learn correlations among feature values as the network monitors and imputes measured input values and also predicts future output values . This computing architecture includes a multi-kernel neural network array with the capability to learn and predict in real time. The CIP also includes a manager and an input-output transducer that may be used for input-output refinement. These components allow the computing capacity of the multi-kernel array to be reassigned in response to measured performance or other factors. The output feature values computed by the multi-kernel array and processed by an output processor of the transducer are supplied to a response unit that may be configured to perform a variety of monitoring, forecasting, and control operations in response to the computed output values.