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Circular convolution, also known as cyclic convolution, is a special case of periodic convolution, which is the convolution of two periodic functions that have the same period. Periodic convolution arises, for example, in the context of the discrete-time Fourier transform (DTFT). In particular, the DTFT of the product of two discrete sequences ...
The premise behind the circular convolution approach on multidimensional signals is to develop a relation between the Convolution theorem and the Discrete Fourier transform (DFT) that can be used to calculate the convolution between two finite-extent, discrete-valued signals.
Rader's algorithm (1968), [1] named for Charles M. Rader of MIT Lincoln Laboratory, is a fast Fourier transform (FFT) algorithm that computes the discrete Fourier transform (DFT) of prime sizes by re-expressing the DFT as a cyclic convolution (the other algorithm for FFTs of prime sizes, Bluestein's algorithm, also works by rewriting the DFT as a convolution).
The circular padding is where the pixel outside wraps around to the other side of the image. The spatial size of the output volume is a function of the input volume size W {\displaystyle W} , the kernel field size K {\displaystyle K} of the convolutional layer neurons, the stride S {\displaystyle S} , and the amount of zero padding P ...
Therefore, the case < is often referred to as zero-padding. Spectral leakage, which increases as L {\displaystyle L} decreases, is detrimental to certain important performance metrics, such as resolution of multiple frequency components and the amount of noise measured by each DTFT sample.
The use of zero-padding for the convolution in Bluestein's algorithm deserves some additional comment. Suppose we zero-pad to a length M ≥ 2N–1. This means that a n is extended to an array A n of length M, where A n = a n for 0 ≤ n < N and A n = 0 otherwise—the usual meaning of "zero-padding".
It is therefore sufficient to compute the N-point circular (or cyclic) convolution of [] with [] in the region [1, N]. The subregion [ M + 1, L + M ] is appended to the output stream, and the other values are discarded .
English: Circular convolution can be expedited by the FFT algorithm, so it is often used with an FIR filter to efficiently compute linear convolutions. These graphs illustrate how that is possible. These graphs illustrate how that is possible.