文件名称:circonv
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圆卷积与线卷积在FIR中的实现,通过程序还开深刻理解两者间的差别和各自优劣。
1.圆卷积用在被截出的某段数据中,此时,长度应该定为和输入数据长度一致(一般输入数据大于hn的数),这时圆卷积结果相当于某段被截断出来的数据以非截断的方式经过滤波而得出的结果;线卷积用在各自独立的,离散的数据中,若截断数据也用线性卷积来计算,那么就相当与这部分数据是与源数据是独立的,
得出的结果时域两端会变长,但频谱基本上一样的。差别可以想象。
2.注意圆卷积最开始的输入数据的次序,构造矩阵时要注意。-Circular convolution with the line convolution in the FIR implementation, the program also opened a deep understanding of the difference between the two and their respective pros and cons. A circular convolution with cut out a certain period of data At this point, the length should be set for the same length as the input data (typically input data greater than hn the number), when the circular convolution is equivalent to a certain the results of the truncated data to the non-truncated filtered line convolution with a separate, discrete data, truncated data with a linear convolution calculation, then the equivalent of this part of the data is independent of the source data, the results of both ends of the time domain becomes long, but the spectrum is basically the same. The difference can imagine. Note that the order of the circular convolution of the input data to construct matrix.
1.圆卷积用在被截出的某段数据中,此时,长度应该定为和输入数据长度一致(一般输入数据大于hn的数),这时圆卷积结果相当于某段被截断出来的数据以非截断的方式经过滤波而得出的结果;线卷积用在各自独立的,离散的数据中,若截断数据也用线性卷积来计算,那么就相当与这部分数据是与源数据是独立的,
得出的结果时域两端会变长,但频谱基本上一样的。差别可以想象。
2.注意圆卷积最开始的输入数据的次序,构造矩阵时要注意。-Circular convolution with the line convolution in the FIR implementation, the program also opened a deep understanding of the difference between the two and their respective pros and cons. A circular convolution with cut out a certain period of data At this point, the length should be set for the same length as the input data (typically input data greater than hn the number), when the circular convolution is equivalent to a certain the results of the truncated data to the non-truncated filtered line convolution with a separate, discrete data, truncated data with a linear convolution calculation, then the equivalent of this part of the data is independent of the source data, the results of both ends of the time domain becomes long, but the spectrum is basically the same. The difference can imagine. Note that the order of the circular convolution of the input data to construct matrix.
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circonv.m
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