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在数字函数发生方法中,微分算法和齐田法形式不同,但就它们的基本特点及发生函数时的误差而言,两者并没有重要的区别。微分法发生的曲线与给定函数之间的误差包括基本误差和走步误差。基本误差系微分法发生曲线时实际逼近的函数(称为逼近函数)与给定函数间的误差。逼近函数可以从给定的函数导出。走步误差为微分法发生曲线与逼近函数间因步法不同而产生的误差。本文证明了用微分法发生二阶、三阶函数时的基本误差相当大,走步误差比基本误差要小得多。
In the method of generating digital functions, the differential algorithm is different from the form of Qi Tian law, but there is no important difference between them in terms of their basic characteristics and errors in the occurrence of a function. The difference between the curve generated by the differential method and the given function includes the basic error and the walking error. The basic error is the difference between the actual approximation function (called the approximation function) and the given function when the differential method occurs. The approximation function can be derived from a given function. Walking error is the difference between the curve generated by the differential method and the approximation function due to different steps. This paper proves that when the second order and third order functions are generated by differential method, the basic error is quite large, and the walking error is much smaller than the basic error.