With the improvements in the data structure and realization, the algorithm took O(NlogN)time, where N is the input size.
经过在数据结构和实现方式上的改进，算法总体平均时间复杂度为O（NlogN）。
The experiment result demonstrates the validity and advantage over general CPU, especially in the condition of large input size. The approach can also be generalized to other transforms alike.
实验结果证明了该实现的有效性，尤其输入数据量较大时，相对于通用CPU计算有明显优势，该方法还可推广于类似数学变换。
The experiment result demonstrates the validity and advantage over general CPU, especially in the condition of large input size. The approach can also be generalized to other transforms alike.
实验结果证明了该实现的有效性，尤其输入数据量较大时，相对于通用CPU计算有明显优势，该方法还可推广于类似数学变换。
应用推荐