微分相关分析的快速算法

W. Pogribny, I. Rozhankiwsky, T. Leszczynski
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引用次数: 0

摘要

相关分析(CA)是DSP的主要组成部分之一,在许多科学技术领域,特别是在计算智能和控制系统中得到了广泛的应用。PCM格式的信号表示允许以指定精度计算相关函数(CF),但同时也会导致大量的多比特运算,导致CA的快速作用不足。因此,在此类任务中,使用不需要乘法的小比特差分方法是方便的。然而,已知的差分CA的方法还没有得到足够的研究。本文的目的是在改进差分PCM (MDPCM)和符号增量调制(SignDM)的基础上,提高噪声信号CA算法的实时性和解析度。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Fast Algorithms of Differential Correlation Analysis
Correlation analysis (CA) is one from main ingredients of DSP and often used in many fields of science and technology particularly in computational intelligence and control systems. Signals representation in PCM format allows to calculate correlation functions (CF) with assign accuracy, however at the same time causes a large number of multi-bit operations and leads to insufficient fast-acting of CA. Therefore, in such tasks it is expedient to use small-bit differential methods without multiplications. However, the known approaches to differential CA are not enough studied. This paper purpose is increasing of the fast-acting and resolution of algorithms of noisy signals CA in real time on the basis of Modified Differential PCM (MDPCM) as well as Sign Delta Modulation (SignDM).
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