Intereting Posts

Rules for Product and Summation Notation
Why are addition and multiplication commutative, but not exponentiation?
Proof that a periodic function is bounded and uniformly continuous.
Variety vs. Manifold
Help Converting to First Logic Order Representation
Has this phenomenon been discovered and named?
Understanding the relationship between differentiation and integration
Establishing a Basis for $F/(f(x))$
How prove this inequality $|x\sin{\frac{1}{x}}-y\sin{\frac{1}{y}}|<2\sqrt{|x-y|}$
Show how to calculate the Riemann zeta function for the first non-trivial zero
Mathematically representing combinations with integers uniquely?
Is a von Neumann algebra just a C*-algebra which is generated by its projections?
$|A \cup B| = \mathfrak{c}$, then $A$ or $B$ has cardinality $\mathfrak{c}$.
Explicit basis for normal closure of $\Bbb Q(\alpha)$ over $\Bbb Q$
Compactness and compact-finite measure in Lusin theorem (Rudin)

Say we have a stochastic process described by a stochastic differential equation (in the Itô sense), and maybe we are able to find an explicit solution of it in terms of deterministic and Itô integrals (and maybe not).

In any of these cases, how can we compute the power spectral density of the process?

For instance, for the Ornstein-Uhlenbeck process, the steps would be

- Strong Markov property of Bessel processes
- Wiener Process $dB^2=dt$
- Independent increments in squared brownian motion
- Strong solutions SDE inequality with an application of Gronwall's inequality
- (Ito lemma proof): convergence of $\sum_{i=0}^{n-1}f(W(t_{i}))(W(t_{i+1})-W(t_{i}))^{2}.$
- martingale and stochastic Integral

- Find autocorrelation function. This is easily done with the Itô isometry and the properties of the Wiener process.
- Compute Fourier transform

And that’s it, because the Wiener-Khinchin theorem assures us that the process autocorrelation and the PSD are a Fourier transform pair as long as the process is wide sense stationary (and the Ornstein-Uhlenbeck process satisfies this). However, The Ornstein-Uhlenbeck process is too nice in reality.

What can be done to obtain the PSD in a more general, non stationary case? What can be then said about the autocorrelation function relation to the PSD? Could you provide any references with theory/worked examples?

For instance, I would really appreciate your help in the not-so-nice (but still nice) second order harmonic oscillator with additive noise term

$$

m\ddot{x} + \gamma\dot{x} + \delta x = \sigma \eta(t)

$$

with

$$

\eta(t) = \frac{\mathrm{d} W_t}{\mathrm{d}t}

$$

(forgive my abuse of notation).

- Derivative of function using discrete fourier transform (MATLAB)
- Number Theoretic Transform (NTT) to speed up multiplications
- Derivative of convolution
- Law of iterated logarithms for BM
- Fourier Transform on the circle
- Fourier Transform of Heaviside
- A funtion and its fourier transformation cannot both be compactly supported unless f=0
- Integral of square of Brownian motion with respect to Brownian Motion
- Multiple self-convolution of rectangular function - integral evaluation
- Fourier Transform of $\frac{1}{(1+x^2)^2}$

*I’ll reply myself with a full derivation of the PSD of the harmonic oscillator. It’s only half of the answer to my original question; the other half can be found here, after I asked the same question on mathoverflow*

The full equation takes the expression

$$

m \ddot{x} + \gamma \dot{x} + \delta x = \sigma \eta(t)

$$

Performing a change of variables, $x = e^{\frac{-\gamma}{2m}t}x_1$, we get

$$

m \ddot{x}_1 + \left(\delta – \frac{\gamma^2}{4m}\right)x_1 = \sigma e^{\frac{\gamma}{2m}t}\eta(t)

$$

thus eliminating $\dot{x}$. Setting $a = \frac{\delta}{m} – \frac{\gamma^2}{4m^2}$, $b = \frac{\sigma}{m}$ and rewriting the equation as a first order linear system with

$$

X =

\begin{pmatrix}

x_2\\

v_2

\end{pmatrix}

$$

where $v_2 = \dot{x_2}$, we get in Ito’s notation

\begin{equation}

X =

\begin{pmatrix}\label{eq:complete}

0 & 1 \\

-a & 0

\end{pmatrix}

\cdot X \mathrm{d}t +

\begin{pmatrix}

0\\

b e^{\frac{\gamma}{2 m}t}

\end{pmatrix}

\cdot \mathrm{d} W_t

\end{equation}

The solution of a linear homogeneous SDE is

$$

X_t = e^{\int_0^t A(t)\mathrm{d}t}\cdot X_0 + e^{\int_0^t A(t)\mathrm{d}t}\cdot \int_0^t e^{-\int A(s)\mathrm{d}s}\sigma(s)\mathrm{d}W_s

$$

where $A(t)$ is the (generally vector) coefficient of $X$. For this SDE a fundamental matrix solution of the associated homogeneous noise-free system is

$$

\Phi(t) =

\begin{pmatrix}

\cos \sqrt{a}t & \sin \sqrt{a}t/\sqrt{a} \\

-\sqrt{a} \sin\sqrt{a}t & \cos \sqrt{a}t

\end{pmatrix}

$$

The determinant of this matrix is 1, so its inverse matrix will be

$$

\Phi^{-1}(t) = e^{-\int A(\tau)\mathrm{d}\tau} = \det \Phi(t)^{-1}\cdot

\begin{pmatrix}

\cos \sqrt{a}t & -\sin \sqrt{a}t/\sqrt{a} \\

\sqrt{a} \sin\sqrt{a}t & \cos \sqrt{a}t

\end{pmatrix}

=

\begin{pmatrix}

\cos \sqrt{a}t & -\sin \sqrt{a}t/\sqrt{a} \\

\sqrt{a} \sin\sqrt{a}t & \cos \sqrt{a}t

\end{pmatrix}

$$

and hence we can solve the complete system. We are interested in the first component of $X$, the position (we will only calculate the PSD of $x$, although this can be done considering the full matrix system)

\begin{equation*}

\begin{split}

x_1(t) = &

\begin{pmatrix}

\cos \sqrt{a}t & \sin \sqrt{a}t/\sqrt{a}

\end{pmatrix}

\cdot

\begin{pmatrix}

x_1(0)\\

v_1(0)

\end{pmatrix}

+

\begin{pmatrix}

\cos \sqrt{a}t & \sin \sqrt{a}t/\sqrt{a}

\end{pmatrix}

\cdot

\int_0^{t}

b e^{\frac{\gamma}{2m}r}\cdot

\begin{pmatrix}

-\sin \sqrt{a}r/\sqrt{a}\\

\cos \sqrt{a}r

\end{pmatrix}

\mathrm{d}W_r

\end{split}

\end{equation*}

Finally, $x_1(t) = e^{\frac{\gamma t}{2m}}x(t)$, so

\begin{equation}

\begin{split}

x(t) = &

e^{-\frac{\gamma t}{2m}}\begin{pmatrix}

\cos \sqrt{a}t & \sin \sqrt{a}t/\sqrt{a}

\end{pmatrix}

\cdot

\begin{pmatrix}

x(0)\\

v(0) + \frac{\gamma}{2m}x(0)

\end{pmatrix}

+\\

&

e^{-\frac{\gamma t}{2m}}

\begin{pmatrix}

\cos \sqrt{a}t & \sin \sqrt{a}t/\sqrt{a}

\end{pmatrix}

\cdot

\int_0^{t}

b e^{\frac{\gamma}{2m}r}\cdot

\begin{pmatrix}

-\sin \sqrt{a}r/\sqrt{a}\\

\cos \sqrt{a}r

\end{pmatrix}

\mathrm{d} W_r

\end{split}

\end{equation}

We see that, after a transient time, only the term depending on $\mathrm{d} W_r$ remains, so the first moment of the process is zero. Now, applying Ito’s isometry to calculate the covariance we get

$$

\mathbb{E} \left[ \int_0^{T} f(u)\,\mathrm{d} W_u \int_0^S f(v) \,\mathrm{d} W_v \right] =

$$

$$

b^2 e^{-\frac{\gamma (t + s)}{2m}}

\begin{pmatrix}

\cos \sqrt{a}t & \sin \sqrt{a}t/\sqrt{a}

\end{pmatrix}

\cdot \mathbb{E} \left[ \int_0^{\min(t,s)}

e^{\frac{\gamma}{m}u}

\begin{pmatrix}

\frac{\sin^2 \sqrt{a}u}{a} & -\frac{\sin \sqrt{a}u \cos \sqrt{a}u}{\sqrt{a}}\\

-\frac{\sin \sqrt{a}u \cos \sqrt{a}u}{\sqrt{a}} & \cos^2 \sqrt{a}u

\end{pmatrix}

\, \mathrm{d} u \right]

\cdot

\begin{pmatrix}

\cos \sqrt{a}s \\

\sin \sqrt{a}s/\sqrt{a}

\end{pmatrix}

$$

This is a quite uninteresting calculation. After simplification one gets

$$

R(\tau) = \frac{b^2 m^2 e^{\frac{-\Gamma |\tau|}{2}}\left( 2 \sqrt{a}m \cos(\sqrt{a}|\tau|) + \gamma \sin(\sqrt{a}|\tau|) \right)}{\sqrt{a}(\gamma^3 + 4a\gamma m^2)}

$$

where we have defined the normalized damping constant $\Gamma = \frac{\gamma}{m}$.

From the expression of the autocorrelation we see that $R(t,\tau) = R(\tau)$: therefore, the process is wide-sense stationary and the conditions to apply the Wiener-Khinchin theorem are satisfied. The Fourier transform of this autocorrelation function is the power spectral density

$$

S(f) = \frac{16b^2}{\Gamma^4 + 8(a + 4\pi^2f^2)\Gamma^2 + 16(a-4\pi^2f^2)^2}

$$

which, after replacing the variables and some rearranging takes the simpler expression

$$

S(\omega) = \frac{\sigma^2/m^2}{(\omega_0^2 – \omega^2)^2 + \Gamma^2 \omega^2}

$$

where we have replaced the unitary ordinary frequency Fourier transform (in terms of $f$) by the non-unitary angular frequency Fourier transform.

- Prove a graph Containing $2k$ odd vertices contains $k$ distinct trails
- Determine the degree of the splitting field for $f(x)=x^{15}-1$.
- Uspenskij-Tkachenko Theorem
- Sources on Several Complex Variables
- How to prove that if each element of group is inverse to itself then group commutative?
- How to Compare powers without calculating?
- Isomorphism between fields
- Optimal algorithm for finding the odd spheres
- Proving theorem connecting the inverse of a holomorphic function to a contour integral of the function.
- Contour Integral: $\int^{\infty}_{0}(1+z^n)^{-1}dz$
- Angle between two vectors?
- On Diophantine equations of the form $x^4-n^2y^4=z^2$
- $a_1=3;\ a_{n+1}=3^{a_n}$; find $a_{2004}\bmod100$
- if $\cos{(a\pi)}=\frac{1}{3}$, then $a $ is irrational
- If $\sum_{1}^{\infty}(a_n)^3$ diverges, does $\sum_{1}^{\infty}(a_n)$?