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Round-off noise estimation of fixed-point algorithms using Modified Affine Arithmetic and Legendre Polynomials

机译:使用修改仿射算术和Legendre多项式的定点算法的圆截面噪声估计

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The implementation of algorithms in fixed-point format causes the apparition of Round-Off Noise which propagates through the different functional units of the system. This issue causes the Signal-to-Noise Ratio of the outputs is degraded. Given an algorithm, it is essential to estimate the integer and fractional bit-widths of all the variables and operations to comply with the Signal-to-Noise Ratio requirements. In this context, Affine Arithmetic can obtain fast and accurate estimations of the bit-widths for linear systems. However, for non-linear systems, Affine Arithmetic loses the temporal correlation of the variables. Other existing frameworks are either time consuming or lead to inaccurate bound estimations. In this paper, a Modified Affine Arithmetic framework with Legendre polynomials is used to obtain fast and accurate bound estimations also for non-linear systems. Moreover, the approach proposed in this paper obtains speedups in the range of 7 to 100 compared to Monte-Carlo simulations.
机译:固定点格式的算法的实现会导致循环噪声的幻影通过系统的不同功能单元传播。此问题导致输出劣化的信噪比。鉴于算法,必须估计所有变量的整数和分数位宽度,以符合信噪比要求。在这种情况下,仿射算法可以获得线性系统的钻头宽度的快速准确估计。然而,对于非线性系统,仿射算术失去了变量的时间相关性。其他现有框架要么耗时,要么导致不准确的累计估计。在本文中,使用具有Legendre多项式的修改的仿射算术框架用于获得非线性系统的快速和准确的伯爵估计。此外,与Monte-Carlo模拟相比,本文提出的方法在7到100的范围内获得了7至100的加速。

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