# definations

$x(t)$ is a function of time. Physically, it can be voltage, displacement, magnetization and so on. It can be real, complex, vectors or more fancy numbers.

$C(t)$ is the auto correlation function of $x(t)$ , defined as:

$$C(t)=\langle x(t) x^*(0) \rangle := \lim_{T\rightarrow \infty}\frac{1}{T}\int_0^T x(t'+t) x^*(t') dt' \tag{1}$$

$I(\omega)$ is the spectrum of $x(t)$, it is the Fourier transformation of $C(t)$, or it is the square of Fourier transformation of $x(t)$. These two definition are equivalent (apply convolution theorem): $$I(\omega)= \int_{-\infty}^{+\infty} C(t) e^{-i\omega t} dt \tag{2}$$

$$I(\omega)= \begin{vmatrix} \int_{-\infty}^{+\infty} x(t) e^{-i\omega t} dt \end{vmatrix}^2 \tag{3}$$

# non-negativity of $I(\omega)$

We can show that, spectrum is non-negative: $$I(\omega)= \begin{vmatrix} \int_{-\infty}^{+\infty} x(t) e^{-i\omega t} dt \end{vmatrix}^2 \geqslant 0$$ And physically it makes sense, because $I(\omega)$ means the energy density within frequency range $[\omega , \omega+d\omega)$.

Energy density shouldn't be negative.

# Question (1): what function $C(t)$ makes its Fourier transform $I(\omega)$ non-negative?

In practice, definition equation (2) is used rather than equation (3).

$C(t)$ is the inverse Fourier tranform of non-negative function $I(\omega)$.

I know some basic law like this: $$\text{FT}[real,even]=real, even$$ $$\text{FT}[real,odd]=imag, odd$$

I have no idea what should $C(t)$ be? $$\text{FT}[???]=real, non \ negative$$ Understand the function class of $C(t)$ might help us solve Question (2), because later on, you will see, I'm doing a transformation to $C(t)$ (essentially it's a discretization), then perform Fourier transform. This discretization transformation might take $C(t)$ out of that class, therefore makes $I(\omega)$ no longer non-negative.

# subtlety in numerics: $I(\omega)$ is no longer non-negative!

In numerical calculations, things become finite and discrete.

Equation (2) is modified to its numeric version:

$$\int \xrightarrow{\text{numerics }} \sum$$ $$\qquad \quad t \xrightarrow{\text{numerics }} t_i \quad i=0,1,2,\cdots,L$$

$$\qquad \quad \omega \xrightarrow{\text{numerics }} \omega_n \quad n=0,1,2,\cdots,L$$ Or, an alternate way to understand numerics is to keep the continues integration, but sample the function $C(t)$ discretely and finitely: $$C(t) \xrightarrow{numerics} C(t) \times \sum_{i=0}^{L-1} \delta(t-t_i)$$

Under this change, $I(\omega)$ is no longer non-negative.

I did some experiments, those negative value of $I(\omega)$ can be as large as 10% of the positive peak value of $I(\omega)$. Adding window function makes things better, but still have 0.1% negative spectrum density.

Only in some commensurate case, $I(\omega)$ is non-negative.

# Question (2): is there any natural way to make $I(\omega)$ non-negative, in numerics?

I find adding absolute value might help $$I(\omega)\rightarrow |I(\omega)|$$ but don't see any reason, such as conservation of energy, so on

So, is there a natural way, to generate non-negative spectrum density, in numerics?

• This sounds purely like a math question – PlasmaHH Jun 13 '18 at 6:48
• Could I convince you to move this to math.se? – a concerned citizen Jun 13 '18 at 6:48
• I think that dsp.stackexchange.com is a better place to ask the question – filo Jun 13 '18 at 7:02
• Think about the use of the complex conjugate in the autocorrelation. That's putting the rabbit into the hat right in front of your eyes. – Neil_UK Jun 13 '18 at 7:10
• Negative frequencies come about because of the direction of phase updating. – analogsystemsrf Jun 18 '18 at 5:07