用于信号和系统分析的离散步进筛选定理

R. Harden, F. Simons
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引用次数: 0

摘要

给出了可以通过求和符号筛选展开和折叠阶跃函数的广义阶跃筛选定理(GSSTs)。这些定理显示出一个不分段的答案,其中包含阶跃函数乘法器,可以在适当的时候打开或关闭这些项。简化的展开函数阶跃筛选定理(SSST-UF)、卷积阶跃筛选定理(SST-C)和恒等式(δ /sub 1/(-n)=1- δ /sub 1/(n-1))可用于求解所有分段卷积问题,无需绘制草图。GSST-UF是最容易记忆的,可以使用上述恒等式用于折叠函数。SSST-UF被证明是最有用的(适用于大约90%的时间)。这些定理可以大大减少信号和系统分析所涉及的劳动,并导致更有意义的见解和解决方案。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Discrete step-sifting theorems for signal and system analyses
Generalized step sifting theorems (GSSTs) that can be used to sift unfolded and folded step functions through the summation sign are presented. The theorems are shown to result in an unsegmented answer that contains step function multipliers that turn the terms on or off at the proper times. The simplified step sifting theorem for unfolded functions (SSST-UF), together with the step sifting theorem for convolution (SST-C) and the identity delta /sub 1/(-n)=1- delta /sub 1/(n-1), can be used to solve all piecewise convolution problems easily without the need for sketches. The GSST-UF is easiest to remember and can be used for folded functions by using the above identity. The SSST-UF proves to be the most useful (applicable about 90% of the time). These theorems can greatly reduce the labor involved in signal and system analysis and lead to more meaningful insight and solutions.<>
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