Signal Processing Stack Exchange is a question and answer site for practitioners of the art and science of signal, image and video processing. It only takes a minute to sign up.
Sign up to join this community
Can someone explain waveshaping to me?
I only know it shapes waveshapes by passing through some functions, but I don't yet understand e.g. what the plots (such as the following in Melda Production MWaveShaper VST-plugin) mean.
Both axes have dB values so I read the axes to be input and output. However, how is the distortion "visualized" in the graph? How does one know how the graph alters audio?
In the audio domain, waveshaping is simply applying a memoryless nonlinear function to an input signal.
$$ y(t) = g\big( x(t) \big) $$
The waveshaping function, $g(x)$, is most often a continuous function that goes through the origin: $g(0)=0$.
Sometimes $g(x)$ is an odd-symmetry function: $g(-x)=-g(x)$, but it doesn't have to be. Sometimes you want 2nd harmonic distortion and then $g(x)$ does not have odd symmetry.
I am more interested in the case where the waveshaping function, $g(x)$ is a polynomial of finite order $N$:
$$ g(x) = \sum\limits_{n=0}^{N} a_n\,x^n $$
Note that if $g(x)$ has even symmetry ($g(-x)=g(x)$), then all odd terms are zero ($a_n=0$ for $n$ odd). If $g(x)$ has odd symmetry ($g(-x)=-g(x)$), then all even terms are zero ($a_n=0$ for $n$ even). I guess, if you want $g(0)=0$, then $a_0=0$.
Now, if the input is sinusoidal:
$$ x(t) = A \cos(2 \pi f_0 t) $$
then the output is periodic, having harmonic frequency components, with an upper limit to the frequency content. The highest frequency coming out will be $N f_0$. So waveshaping with polynomial mapping functions guarantees a limit to the highest frequencies generated and that can be useful in deciding an oversampling ratio necessary to guard against aliasing. As I alluded to in this answer, if the order of the polynomial is $N$, to insure against aliases folding back into your original passband, one must oversample with an upsampling ratio of at least $\frac{N+1}{2}$. Oversampling by 4x sufficies for a 7th-order polynomial.
Also note that an even-symmetry polynomial will generate only even harmonics and an odd-order polynomial will generate only odd harmoncs.
$$\begin{align} y(t) &= g\big( x(t) \big) \\ \\ &= \sum\limits_{n=0}^{N} a_n\,\big(x(t)\big)^n \\ \\ &= \sum\limits_{n=0}^{N} a_n\,\big(A \cos(2 \pi f_0 t)\big)^n \\ \\ &= \sum\limits_{k=0}^{N} b_k \cos(2 \pi k f_0 t) \\ \end{align}$$
where the $b_k$ coefficients depend on the $a_n$ coefficients and the input amplitude of $A$. This relationship can be worked out using the Euler identity and the binomial theorem:
$$\begin{align} y(t) &= g\big( x(t) \big) \\ \\ &= \sum\limits_{n=0}^{N} a_n\,\big(A \cos(2 \pi f_0 t)\big)^n \\ \\ &= \sum\limits_{n=0}^{N} a_n\,\left(\tfrac{A}{2}(e^{j 2 \pi k f_0 t}+e^{-j 2 \pi k f_0 t})\right)^n \\ \\ &= \sum\limits_{n=0}^{N} a_n\,\left(\tfrac{A}{2}\right)^n\left(e^{j 2 \pi f_0 t}+e^{-j 2 \pi f_0 t}\right)^n \\ \\ &= \sum\limits_{n=0}^{N} a_n\,\left(\tfrac{A}{2}\right)^n \sum\limits_{m=0}^{n} \frac{n!}{m!(n-m)!} (e^{j 2 \pi f_0 t})^m (e^{-j 2 \pi f_0 t})^{n-m} \\ \\ &= \sum\limits_{n=0}^{N} a_n\,\left(\tfrac{A}{2}\right)^n \sum\limits_{m=0}^{n} \frac{n!}{m!(n-m)!} e^{j 2 \pi m f_0 t} e^{-j 2 \pi (n-m) f_0 t} \\ \\ &= \sum\limits_{n=0}^{N} a_n\,\left(\tfrac{A}{2}\right)^n \tfrac12 \left(\sum\limits_{m=0}^{n} \frac{n!}{m!(n-m)!} e^{j 2 \pi m f_0 t} e^{-j 2 \pi (n-m) f_0 t} \\ + \sum\limits_{m=0}^{n} \frac{n!}{m!(n-m)!} e^{j 2 \pi m f_0 t} e^{-j 2 \pi (n-m) f_0 t} \right) \\ \\ &= \sum\limits_{n=0}^{N} a_n\,\left(\tfrac{A}{2}\right)^n \tfrac12 \left(\sum\limits_{m=0}^{n} \frac{n!}{m!(n-m)!} e^{j 2 \pi m f_0 t} e^{-j 2 \pi (n-m) f_0 t} \\ + \sum\limits_{m=0}^{n} \frac{n!}{m!(n-m)!} e^{j 2 \pi (n-m) f_0 t} e^{-j 2 \pi m f_0 t} \right) \\ \\ &= \sum\limits_{n=0}^{N} a_n\,\left(\tfrac{A}{2}\right)^n \tfrac12 \left(\sum\limits_{m=0}^{n} \frac{n!}{m!(n-m)!} e^{j 2 \pi (2m-n) f_0 t} + \sum\limits_{m=0}^{n} \frac{n!}{m!(n-m)!} e^{j 2 \pi (n-2m) f_0 t} \right) \\ \\ &= \sum\limits_{n=0}^{N} a_n\,\left(\tfrac{A}{2}\right)^n \tfrac12 \sum\limits_{m=0}^{n} \frac{n!}{m!(n-m)!} \left( e^{j 2 \pi (n-2m) f_0 t} + e^{-j 2 \pi (n-2m) f_0 t} \right) \\ \\ &= \sum\limits_{n=0}^{N} \sum\limits_{m=0}^{n} a_n\,\left(\tfrac{A}{2}\right)^n \frac{n!}{m!(n-m)!} \tfrac12 \left( e^{j 2 \pi (n-2m) f_0 t} + e^{-j 2 \pi (n-2m) f_0 t} \right) \\ \\ &= \sum\limits_{n=0}^{N} \sum\limits_{m=0}^{n} a_n\,\left(\tfrac{A}{2}\right)^n \frac{n!}{m!(n-m)!} \cos \big(2 \pi (n-2m) f_0 t \big) \\ \\ ... \\ &= \sum\limits_{k=0}^{N} b_k \cos(2 \pi k f_0 t) \\ \end{align}$$
Okay, to get an expression for $b_k$, the only way I can figger it out is for three cases. We let $k=n-2m$ and observe that since $2m$ is always even, only even $n$ terms contribute to $b_k$ when $k$ is even. Likewise, only odd $n$ terms contribute to $b_k$ when $k$ is odd.
The expression $\lfloor N/2 \rfloor$ is the floor() function applied to $N/2$. just round $N/2$ down to the nearest integer.
Case 1, $k=0$ (the DC term) Only the even terms of $n$ will contribute to $b_0$. And the only term of the inside summation that contributes is that when $m=\tfrac{n}{2}$. So letting $n=2i$:
$$ b_0 = \sum\limits_{i=0}^{\lfloor N/2 \rfloor} a_{2i}\,\left(\tfrac{A}{2}\right)^{2i} \frac{(2i)!}{\big((i)!\big)^2} $$
In the following two cases, keep in mind that the $\cos()$ function is even symmetry and these two terms are equal:
$$ \cos(2 \pi (-k) f_0 t) = \cos(2 \pi k f_0 t) $$
Case 2, $k$ even, $k>0$ (even harmonics) Only the even terms of $n$ will contribute to $b_k$. The only two term of the inside summation that contribute are those where $m=\tfrac{n-k}{2}$ and $m=\tfrac{n+k}{2}$ . So letting $n=2i$:
$$ b_k = \sum\limits_{i=0}^{\lfloor N/2 \rfloor} a_{2i}\,\left(\tfrac{A}{2}\right)^{2i} \frac{2(2i)!}{(i-\tfrac{k}{2})!(i+\tfrac{k}{2})! } \qquad k>0 \text{ even} $$
Terms with $i<\tfrac{k}{2}$ will result in $\infty$ in the denominator because factorials of negative integers are infinite. That effectively modifies the bottom limit:
$$ b_k = \sum\limits_{i=k/2}^{\lfloor N/2 \rfloor} a_{2i}\,\left(\tfrac{A}{2}\right)^{2i} \frac{2(2i)!}{(i-\tfrac{k}{2})!(i+\tfrac{k}{2})! } \qquad k>0 \text{ even} $$
Case 3, $k$ odd, $k>0$ (odd harmonics) Only the odd terms of $n$ will contribute to $b_k$. The only two term of the inside summation that contribute are those where $m=\tfrac{n-k}{2}$ and $m=\tfrac{n+k}{2}$. So letting $n=2i+1$:
$$ b_k = \sum\limits_{i=0}^{\lfloor (N-1)/2 \rfloor} a_{2i+1}\,\left(\tfrac{A}{2}\right)^{2i+1} \frac{2(2i+1)!}{(i-\tfrac{k-1}{2})!(i+\tfrac{k+1}{2})!} \qquad k>0 \text{ odd} $$
Terms with $i<\tfrac{k-1}{2}$ will result in $\infty$ in the denominator because factorials of negative integers are infinite. That effectively modifies the bottom limit:
$$ b_k = \sum\limits_{i=(k-1)/2}^{\lfloor (N-1)/2 \rfloor} a_{2i+1}\,\left(\tfrac{A}{2}\right)^{2i+1} \frac{2(2i+1)!}{(i-\tfrac{k-1}{2})!(i+\tfrac{k+1}{2})!} \qquad k>0 \text{ odd} $$
.
(i wouldn't mind if someone else checked my math. these results tell us something about how a polynomial waveshaping function will sound, at least what the amplitude of harmonics will be.)
