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linear convolution using circular
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matlab..rar gives some matlab codes like am modulation, circular convolution and pdf distributions which is easy to understand
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matlabb.rar gives codes for am modulation, linear convolution, circular convolution, pdf distributions which are easy to understand.
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线性卷积和循环卷积在工程上的应用亦非常广泛，在Matlab软件处理下，实现任意两个序列的线性和循环卷积对于工程上的辅助是相当重要的，程序为读者提供了线性卷积和循环卷积的matlab编码。-Linear convolution in engineering application is very extensive, in MATLAB software, to achieve any two sequences of linear and circular convolution support
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是DSP的圆卷积教程，内部有循环相加和循环保留两种的方法-DSP tutorial is circular convolution, adding internal circulation and recycling methods to retain two of them
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数字处理课程设计的程序，里面包括有褶积滤波，快变滤波，褶积滤波与递归滤波的比较，设计高通滤波因子，分析补零对振幅谱的影响，线性褶积和循环褶积，最小平方反滤波，零相位转换，最小相位转换，对地震记录进行静校正11个程序-Digital Processing course design program, which includes the convolution filter, quick change filter, compare convolution filtering and recurs
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计算普通褶积与循环褶积，分别使用时间域与频率域两种方法进行正、反演计算，指出循环褶积计算时所存在的边界效应现象；编写一个做相关分析的源程序-Calculation ordinary convolution and circular convolution, respectively, using the time domain and frequency domain in two ways positive, inverse calculation, noted the phenomenon
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E ective image compression requires a non-expansive discrete wavelet transform (DWT) be
employed consequently, image border extension is a critical issue. Ideally, the image border
extension method should not introduce distortion under compressio
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实现线性卷积和循环卷积的动画演示
具体操作看代码-Achieve circular convolution and linear convolution of animation
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内附实验报告、源码及参考资料。1.周期卷积、循环卷积和线性卷积比较，2.DFT性质探究-Enclosing the lab reports, source code and reference materials. 1. Periodic convolution, circular convolution and linear convolution comparison, 2.DFT explore nature
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基于循环卷积神经网络的图像处理，可用于图像的模式识别-Based on circular convolution neural network image processing, pattern recognition can be used in the image
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circular convolution
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理解频域处理与空间域处理的等效关系与步骤，掌握频域相乘与空间域循环卷积之间的对等关系，理解DFT运算中补零的效果。(Understand the equivalent relationship and steps of frequency domain processing and space domain processing, understand the reciprocal relationship between frequency domain multiplication and
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