Two-dimensional curve fitting and prediction using spectral analysis

A curve-fitting or prediction problem for two-dimensional or cyclic processes is defined and solved using spectral techniques. The assumed statistical model is structurally similar to the Karhunen-Lo¿¿ve expansion, and the technique can be implemented using the singular-value decomposition. Two examples using published data illustrate the feasibility of the method and the peculiarities associated with the problem.