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Cyclic convolution on via the DFT
Example
On let , that is and , and similarly for . Their unnormalised transforms of The unnormalised engineering DFT and its conversion to the unitary transform are ; the convolution law in engineering form gives componentwise, that is , and inverse transforming by returns . Direct evaluation of the cyclic convolution of The unnormalised cyclic convolution on gives the same tuple . In this instance the length is large enough that no coefficient wraps, so the cyclic convolution equals the linear convolution of the coefficient sequences.
Facts & Assumptions
Given: The functions with and , and the classes of .
for , and ; the inverse formula of length is (The unnormalised engineering DFT and its conversion to the unitary transform, The unitary discrete Fourier transform on , Finite Fourier inversion for the unitary transform on , Rational powers of a positive base, Laws of rational exponents).
The cyclic convolution is , a finite sum depending on classes only (The unnormalised cyclic convolution on ), and the transform law in engineering form is for every , obtained from and (The DFT turns cyclic convolution into a scaled pointwise product, [F1]).
Exponential values: , , , (, , and , , and exactly when , The complex exponential by its power series); hence and for (, and the complex exponential extends the real exponential).
Field arithmetic in : , , , and , ( is a field, every element is uniquely , and every nonzero element has inverse ).
Verification
Transform values: for by [F1] and [L1], so , , and by [L2]; thus , and the same values hold for since .
Direct evaluation of the convolution: ; ; ; , where and by [L3]. Hence .
Product in the transform domain: by [F2], so componentwise , , and , giving .
Inverse transforming step 2.1: by [F1], for by [L1]; at this is , at it is , at it is , and at it is , where is used throughout. So the inverse transform returns , in agreement with the direct computation of step 1.2. Since , no coefficient wraps and the cyclic convolution equals the linear convolution of the coefficient sequences.
Remarks
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What the computation shows and what it does not. It shows the transform law of [F2] producing a genuine cyclic convolution and agreeing with direct summation for one four-point pair. It does not claim that a length- transform is efficient — the point of the example is the normalisation bookkeeping: with unnormalised the product law has no extra factor, while with the same computation carries the factor .
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The wrap-free regime. Because the coefficient lists have length each and the product has coefficients, the four-point cyclic convolution sees no wrap. The companion counterexample shows what changes at length , where the product's third coefficient wraps back into degree .
Depends on
- $\exp(x+iy)=e^x(\cos y+i\sin y)$, $|\exp(x+iy)|=e^x$, and $e^{i\pi}+1=0$
- The complex exponential by its power series
- The unnormalised cyclic convolution on $\mathbb Z/N\mathbb Z$
- The congruence class $[a]_n$ and the quotient set $\mathbb{Z}/n$
- Rational powers $a^r$ of a positive base
- The unitary discrete Fourier transform on $\mathbb Z/N\mathbb Z$
- The unnormalised engineering DFT and its conversion to the unitary transform
- The DFT turns cyclic convolution into a scaled pointwise product
- Laws of rational exponents
- $\mathbb C=\mathbb R[x]/(x^2+1)$ is a field, every element is uniquely $a+bi$, and every nonzero element has inverse $(a-bi)/(a^2+b^2)$
- $\exp(z+w)=\exp z\,\exp w$, and the complex exponential extends the real exponential
- Finite Fourier inversion for the unitary transform on $\mathbb Z/N\mathbb Z$
- For every natural $n$, $(\mathbb{Z}/n,+)$ is an abelian group, multiplication is a commutative monoid operation, and both distributive laws hold
- $\ker(\exp)=2\pi i\mathbb Z$, and $\exp z=\exp w$ exactly when $z-w\in2\pi i\mathbb Z$
- For $n\ge 1$, every class in $\mathbb{Z}/n$ has one representative $r$ with $0\le r<n$, so $\lvert\mathbb{Z}/n\rvert=n$; while $\mathbb{Z}/0$ is in bijection with $\mathbb{Z}$
Used by
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Sources
- Michael E. Taylor, Fourier Analysis, Distributions, and Constant-Coefficient Linear PDE (author PDF) (standard reference, not scraped)