DocumentCode :
637162
Title :
Optimum quantizing of monotonic nondecreasing arrays
Author :
Hsu, William W. Y. ; Cheng-Yu Lu ; Ming-Yang Kao ; Jan-Ming Ho
Author_Institution :
Dept. of Comput. Sci. & Eng., Nat. Taiwan Ocean Univ., Keelung, Taiwan
fYear :
2013
fDate :
16-19 April 2013
Firstpage :
95
Lastpage :
101
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.
Keywords :
computational complexity; convex programming; O(kn) time algorithm; continuous-to-discrete transformation; convex hull; dynamic programming algorithm; heuristic algorithm; monotonic nondecreasing arrays; naïve approach; optimal k-cuts; Algorithm design and analysis; Dynamic programming; Equations; Heuristic algorithms; Partitioning algorithms; Predictive models; Quantization (signal); Maximum Area; Monotonic Nondecreasing Convex Arrays; Quantization;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computational Intelligence for Financial Engineering & Economics (CIFEr), 2013 IEEE Conference on
Conference_Location :
Singapore
Type :
conf
DOI :
10.1109/CIFEr.2013.6611703
Filename :
6611703
Link To Document :
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