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Analytical method for optimum non-negative integer bit allocation

机译:最佳非负整数位分配的解析方法

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The optimum bit allocation (OBA) problem was first investigated by Huang and Schultheiss in 1963. They solved the problem allowing the bits to be signed real numbers. Later, different algorithms were proposed for OBA problem when the bits were constrained to be integer and non-negative. In 2006, Farber and Zeger proposed new algorithms for solving optimum integer bit allocation (OIBA) and optimum non-negative integer bit allocation (ONIBA). None of the existing algorithms for OIBA and ONIBA problems end with an analytical solution. In this study, a new analytical solution is proposed for OIBA and ONIBA problems based on a novel analytical optimisation approach. At first, a closed form solution is derived for Lagrange unconstraint problem. Then, by removing the Lagrange multiplier, an analytical solution is obtained for OIBA and ONIBA problems. Using the selection and bisection algorithms, a low complexity algorithm is proposed for searching in a group of discrete functions which can reduce the computational complexity of the analytical solution. The complexity of computing the analytical solution is O(k) which is much lower than the complexity of existing ONIBA algorithms.
机译:Huang和Schultheiss于1963年首先研究了最佳比特分配(OBA)问题。他们解决了使比特成为实数的问题。后来,当位被限制为整数和非负数时,针对OBA问题提出了不同的算法。在2006年,Farber和Zeger提出了用于求解最佳整数位分配(OIBA)和最佳非负整数位分配(ONIBA)的新算法。现有的OIBA和ONIBA问题算法都没有以解析解决方案结尾。在这项研究中,基于一种新颖的分析优化方法,针对OIBA和ONIBA问题提出了一种新的分析解决方案。首先,导出了拉格朗日无约束问题的闭式解。然后,通过删除拉格朗日乘数,可以获得OIBA和ONIBA问题的解析解。使用选择和二等分算法,提出了一种低复杂度算法,用于在一组离散函数中进行搜索,可以降低解析解的计算复杂度。计算分析解决方案的复杂度为O(k),远低于现有ONIBA算法的复杂度。

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