System for continuous logic computation and method of using same

A continuous logic system using a neural network is characterized by defining input and output variables that do not use a membership function, by employing production rules (IF/THEN rules) that relate the output variables to the input variables, and by using the neural network to compute or interpolate the outputs. The neural network first learns the given production rules and then produces the outputs in real time. The neural network is constructed of artificial neurons each having only one significant processing element in the form of a multiplier. The neural network utilizes a training algorithm which does not require repetitive training and which yields a global minimum to each given set of input vectors.