Mathematics Stack Exchange is a question and answer site for people studying math at any level and professionals in related fields. It's 100% free, no registration required.

Sign up
Here's how it works:
  1. Anybody can ask a question
  2. Anybody can answer
  3. The best answers are voted up and rise to the top

Background: I need some help to understand the concept behind measure-driven differential equations. The solution of an ordinary differential equation is continuous. In order to describe discontinuous trajectories we use the concept of distributions (very well described in the book "Functional Analysis" by W. Rudin). In brief, every function $x:\Re\to\Omega\subseteq \Re^n$ that is locally integrable over the open set $\Omega$ is mapped to a functional $T_x:\mathcal{D}(\Re^n)\to\Re^n$ as follows:

$$ T_x(\phi)= \int_\Omega x\phi d\mu $$

where $\mathcal{D}(\Re^n)$ is the set of test functions (infinitely many times differentiable and with compact support). $\mu$ is the Lebesgue measure over $\Omega$ - meaning that the integration is carried out in the Lebesgue sense.

Every distribution (i.e. a functional $T\in\mathcal{D}^\star(\Omega)$) has a derivative given by:

$$ (DT)(\phi)=-T(D\phi) $$

In that sense we can construct generalized differential equations that look like:

$$ DT=g(T) $$

Using this framework we can describe solutions that encounter jumps such as impulsive differential equations. This is accomplished using the Dirac functional $\delta(\phi)=\phi(0)$. (I don't want to go into much detail to keep the question short).

The problem: I recently stumbled on a thing called "Measure-driven differential equations". These have the form:

$$ dx=f(x(t),u(t))dt+g(x(t))d\mu(t) $$

where $\mu:\mathcal{B}([t_0,t_1])\to\Re_+$ is a positive measure with the property $\mu(A)\in K$ for all $A\subseteq [t_0,t_1]$ where $K$ is compact. $u$ and $\mu$ here serve as external "signals". The solution of such an equation is reportedly:

$$ x(t)=x(t_0) + \int_{t_0}^t f(x(s),u(s))ds + \int_{[t_0,t]}g(x(s))\mu(ds) $$

(see this article for example).

The questions: (i) I'm a bit puzzled with the notation $d\mu(t)$ and $\mu(ds)$. Can someone elaborate a bit on that? Since $\mu$ is a measure, what exactly is the meaning of $\mu(ds)$? (ii) Is there any advantage from using measures instead of distributions to describe phenomena with discontinuous trajectories? (iii) I would appreciate some reference (preferably a book) to get started with these things.

share|cite|improve this question
For (i), the Lebesgue integral of the function $f$ w.r.t. measure $\mu$ over the set $A$ is often denoted either by $$ \int\limits_A d\mathrm d\mu $$ or by $$ \int\limits_A f(x)\mu(\mathrm dx). $$ These notations are equivalent and are chosen based on personal preferences/notation convenience. I guess, when the measure-driven ODE is written, the form $\mathrm d\mu(t)$ is chosen to hold the similarity with $\mathrm dt$ (usual increment in ODEs) or $\mathrm dB_t$ (Brownian motion's increment in SDEs) – Ilya Aug 27 '12 at 8:13
The first integral was meant to be $\int_A f\mathrm d\mu$ – Ilya Aug 29 '12 at 13:46

Your Answer


By posting your answer, you agree to the privacy policy and terms of service.

Browse other questions tagged or ask your own question.