Optimum quantizing of monotonic nondecreasing arrays

William W. Y. Hsu, Cheng-Yu Lu, M. Kao, Jan-Ming Ho
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Abstract

This paper presents an efficient algorithm for finding the optimal k-cuts of a nondecreasing array of size n that produces the maximum area under the points. The naïve approach uses a dynamic programming algorithm which requires O(kn2) time, where n is the size of the array. This algorithm is time consuming for large n or k and thus inappropriate. We design faster algorithms by discovering and proving some nice properties of the nondecreasing arrays, finding convex hull, and by continuous-to-discrete transformation. We believe that an O(kn) time algorithm exists and show a heuristic algorithm.
单调非递减阵列的最佳量化
本文提出了一种求大小为n的非递减数组的最优k-cut的有效算法,该算法使点下的面积最大。naïve方法使用动态规划算法,需要O(kn2)时间,其中n是数组的大小。对于较大的n或k,该算法非常耗时,因此不合适。我们通过发现和证明非递减数组的一些很好的性质,寻找凸包,以及通过连续到离散的变换来设计更快的算法。我们认为存在一个耗时O(kn)的算法,并给出了一个启发式算法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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