ideal low pass filter the anti aliasing filter function f n is determined according to the following formula hence the coefficients of the anti aliasing function are determined by multiplying together the hamming window coefficients and the ideal low pass filter coefficients that were determined as described above the design of the anti aliasing filter is automatic once the window order n is chosen as the coefficients for the hamming window are based on n and the coefficients for the ideal low pass filter are based on the window order n and the number of minislices per control slice generally a large n is better but this may be limited by computation or computer memory by way of example fig5 a 5b are graphs showing the response of a 20the order hamming function and an ideal low pass filter fig6 is a graph of an anti aliasing filter constructed according to the present invention by convolving the hamming window response of fig5 a and the low pass filter response of fig5 b as shown in fig2 the anti aliasing filter of fig6 is applied to the n datapoints of the high resolution profile 40 to produce an intermediate filtered profile 42 that is then decimated to produce a final low resolution control profile 45 following are two examples of the manner in.