Abstract:
A system polynomial is determined using a plurality of system I/O data, wherein the system polynomial expresses the system output (98) in terms of the system input (96), and wherein the system polynomial has r' terms including at least one linear term and at least one nonlinear term, the r' terms found using a regression subsets technique. A control polynomial (90) is determined, the control polynomial (90) having at least one cancellation term and at least one control term, the at least one cancellation term calculated to cancel the at least one nonlinear term of the system polynomial, and the at least one control term calculated to control the at least one linear term of the system polynomial. A control output (92) signal is generated based on the control polynomial (90) and the control input signal (94).
Abstract:
In a polynomial processor (10) a plurality of training data are received which express the desired relationship between the processor's output and input. The terms of a polynomial function are determined using a regression subsets method on the training data. The coefficients for each term are determined and the polynomial processor (10) is programmed by loading the terms and coefficients into the processor.
Abstract:
A wide-angle lens (12) produces a distorted wide-angle optical image. An imaging sensor (14), having a surface in optical communication with the wide-angle lens, converts the wide-angle optical image into a corresponding output signal. The imaging sensor includes a plurality of imaging elements (20). The plurality of imaging elements have a distribution on the surface of the sensor that is representable by a nonlinear function, wherein the distribution of the imaging elements corrects the distortion in the wide-angle image.