Citation/Abstract

This dissertation presents a general framework for the complex-step derivative approximation to compute numerical derivatives. For first derivatives the complex-step approach does not suffer subtraction cancellation errors as in standard numerical finite-difference approaches. Therefore, since an arbitrarily small step-size can be chosen, the complex-step method can achieve near analytical accuracy. However, for second derivatives straight implementation of the complex-step approach does suffer from roundoff errors. Therefore, an arbitrarily small step-size cannot be chosen. This dissertation expands upon the standard complex-step approach to provide a wider range of accuracy for both the first and second derivative approximations. Higher accuracy formulations can be obtained by repetitively applying the Richardson extrapolations. The new extensions can allow the use of one step-size to provide optimal accuracy for both derivative approximations. Simulation results are provided to show the performance of the new complex-step approximations on a second-order Kalman filter. The new first and second derivatives are also used to generalize the second-order Divided Difference filter to incorporate the complex-step approach.