Standard Recursive Method Research Articles

New Fourier methods for generation system production costing

Two new, robust, and computationally efficient Fourier methods for solving the probabilistic production costing problem are presented. The method first proposed yields closely matching results with those of the standard recursive method, which is an exact method. The second method that is proposed is less accurate, but about three times as fast as the first method. Both methods offer substantial computational savings over the standard recursive method. A model test system is used to illustrate the performance of the proposed methods vis-a-vis that of the standard recursive method.

漸化フィルター法による加速度記録解析

To obtain near-field ground motions, both strong-motion seismographs and long-period seismographs were operated in the epicentral region of Mount Usu, Hokkaido, Japan. The earthquake swarm had occurred there since 1977, and hundreds of earthquakes of magnitudes from 2.1 to 4.4 were recorded on the digital recorder during the period from August, 1979 to July, 1980. The epicentral distances are all 3km and less. Using these seismograms we develop a new and efficient procedure for calculating velocities and displacements from digital strong-motion accelerograms. In the filtering operation we use a Chebyshev causal digital-filter with the automatic design algorithm described by M. Saito. This operation is applied in time domain by using a . standard recursive method, and preserves properties of the actual ground motion. A distortion in the calculated displacements is found very little in comparison with the actual ones. The application of the present method to strong-motion accelerograms will make the time-domain analysis easy and reliable.

Error analysis for Fourier series evaluation

A floating-point error analysis is given for the standard recursive method of evaluating trigonometric polynomials. It is shown that, by introducing a phase-shift, one can hold the error growth down to an essentially linear function of the degree. Explicit computable error bounds are derived and numerically verified.