Questions on the (continuous or discrete) convolution of two functions. It can also be used for questions about convolution of distributions (in the Schartz's sense) or measures.

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How to calculate convolution of function defining a measure

Given the function $F(t)=2-2e^{-t}$ defining a measure on $(\mathbb{R}_+,\mathfrak{B}(\mathbb{R}_+))$ and I want to calculate the convolution of this function with itself. I tried to do that by using ...
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10 views

norm bounded Convolution in matrix space

There is a stable matrix $A$ with eigen values in unit circle,for discrete time system : $x(k+1)=Ax(k)+f(k)$ can we prove: $||\Sigma_{j=0,..,k} A^{k-j}f(j)||_2<= ||f(k)||_2/{(1-A_{max})} $ where ...
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1answer
21 views

Sum of uniformly distributed random variables in a given range

I am trying to find the sum of n uniformly distributed i.i.d random variables in the range [0-W]. I am aware that if the variables are distributed in the interval (0,1) then their convolution is given ...
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13 views

Calculate FFT of 1/r green's function

I am trying to write the Poisson equation solver in C, using FFTW library. For given density of charge I need to calculate potential assuming periodic boundaries. My idea is to use convolution, simply ...
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1answer
36 views

How to find solution of the integral equation?

$$y(t) + t \int_0^t y(v)dv = 1 + \int_0^t vy(v)dv$$ I found the answer to be $y(t) = \cos{t}$. I have no idea how they go this answer. I would appreciate any suggestions how to solve this.
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1answer
32 views

Does convolution preserve strict log-concavity?

Suppose $f, g$ are strictly log-concave functions. Then the convolution $f * g$ will also be log-concave. However, will it also be strictly log-concave? Thanks!
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2answers
52 views

Convolution of discrete uniform distributions

For two independent, discrete, uniformly distributed random variables $X$ and $Y$, I wish to obtain the distribution of the sum $Z=X+Y$. I have the densities: $$f_X(x)=\left\{\begin{matrix} ...
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17 views

Product of two random variables - Resulting Distribution and Correlation?

Let $X \sim \mathcal{N}(0,1)$ and let $Z$ be a random variable independent of $X$ such that \begin{align*} P(Z=z) = \begin{cases}\frac{1}{2} & z=-1\\ \frac{1}{2} & z = 1\\ 0 & ...
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40 views

What is a convolution kernel?

What is a convolution kernel? (in measure theory, probability theory) In which book can I read about kernels on measurable spaces and convolution kernels? Thank you!
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14 views

Convolution integral

I got unfortunally stuck by performing a (quite simple?) convolution integral. Given are those functions: $$f_1(t) = k_1\cdot e^{b_1\cdot t}$$ and $$f_2(t) = k_2\cdot t$$ where $k_1, k_2$ and $b_1$ ...
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72 views

A problem with kernels on measurable spaces

Let $(E, \mathcal{B}(E)), (F, \mathcal{B}(F))$ be two measurable spaces. A $kernel$ from $(E, \mathcal{B}(E))$ to $(F, \mathcal{B}(F))$ is an application $N : p \mathcal{B} (E) \rightarrow p ...
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1answer
20 views

Calculating PDF of $Z$ from $X,Y$ when $Z=X+Y$, given the PDFs of $X$ and $Y$

A Student is taking an exam which has two parts, X and Y, with each part given a score from 200 to 800. The students probability distribution for each part is given by $$ f_X(x)= \begin{cases} ...
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15 views

Inverse Laplace transformation correct?

I'm actually on the way to solve a little bit complicated differential-equation. Therefore I used the Laplace transformation. I've already solved it but I am actually not sure, whether my solution ...
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0answers
12 views

Exponential decay convolved with a gaussian

I need to convolve an exponential decay (defined as the exponential $Ae^{-\lambda t}$ from $0$ to $+\infty$) with a Gaussian of known standard deviation $\sigma$, in other words I need to compute the ...
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0answers
16 views

Is it true that for every signed probability distribution `f`, there are positive distributions `g` and `h` st. `fg=h`?

While reading the article Half of a Coin: Negative Probabilities, I came across the following theorem: For every generalized g.f. f (of a signed probability distribution) there exist two ...
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1answer
19 views

Convolution Theorem involving a constant.

Should one have f(x) and g(x), and wants $f(x) \ast g(x) $ from what i understand this can be quite difficult, however should $f(x)=\alpha$, a constant, what is $f(x) \ast g(x) $?
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28 views

Laplace transform involving two functions of t

I need to solve the following $$ \int_0^{\infty} f(t)g(t)e^{rt} dt$$ Where $$g(t)=t^n$$ Letting r=-s we have the definition of $$ \mathcal{L} [ f(t)g(t) ]$$ and am unsure how to continue.
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18 views

Discretization of a convolution integral for constrained optimization problem

I'm working on a constrained optimization problem in which an unknown forcing function, $u(\eta)$, is in the integrand of a convolution integral. To find an optimal shape for $u(\eta)$, the integral ...
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2answers
32 views

Finding convolution of exponential distribution

So this is a probability question, and I am asked to find $P(0.6 < Y <= 2.2)$ where $Y = X_1 + X_2$ X1~U(0,1) and X2~exp(2). Our professor worked it out, but I do not understand his ...
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1answer
16 views

Solving convolution $f(t)*g(t)$ where $f(t) = u(t) - u(t-2)$ and $g(t) = e^{-2t}u(t)$ where $u(t)$ is heaviside step function

How does one solve convolution $f(t)*g(t)$ where $f(t) = u(t) - u(t-2)$ and $g(t) = e^{-2t}u(t)$ where $u(t)$ is heaviside (unit) step function? I tried using Fourier transform of both functions to ...
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1answer
34 views

Solve initial value problem with unspecified right-hand side $g(t)$

Consider the initial value problem $$y''-6y'+9y=g(t),\quad y(0)=1,\ y'(0)=3.$$ 1) Use the Convolution Theorem to find the solution to the IVP for any piecewise continuous function $g(t)$ that is of ...
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1answer
41 views

Young's inequality for convolutions

Let's assume that the convolution $f * g$ is continuous with $\lim_{|x| \to \infty}(f*g)(x) = 0$ and that $f, g \in L^2$. Then the following inequality holds $$ \| f * g \|_{\infty} \leq \| f \|_2 ...
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0answers
19 views

Convolution of two bernoulli distributions

Find the probability mass function of the sum of X ∼ Bernoulli(p) and an independent Y ∼ Bernoulli(q) variable. I started by letting Z=X+Y So $$P_z(Z)= \sum_{i=0}^{1}f_x(x) f_y(z-x) $$ $$ ...
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8 views

“Flipping and shifting” in discrete time convolution

I was watching this video to better understand discrete time convolution. I was told to convolve graphically, take one of the signals and flip it about the time axis, and shift it along the other ...
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8 views

Approximation technique of common probability distributions that can be convoluted and integrated fast

I am looking for a approximation technique of functions with two conditions: It is possible to perform a fast approximate convolution with the approximate functions. It is possible to numerically ...
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1answer
18 views

Convolution with heaviside function, argument of the heaviside carry on to the dirac function?

So I have this equation to demonstrate: $$ x(t)*u(t)= \int_{-\infty}^t x(\tau)d\tau $$ , where $u(t)=\int_{-\infty}^t \delta(\tau)d\tau$ I opened the convolution as $ \int_{-\infty}^\infty ...
2
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1answer
93 views

Convolution of sine and unit step function

I started studying signal convolution recently and the first sample problem I got is to find convolution of sine and unit step function (Heaviside function). Here is what I have right now. ...
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1answer
21 views

Convolution CDF formula?

In reference to this post, the pdf of dependent random variables $A+B$ is given by: $$f_{A+B}(z) = \int_{-\infty}^{\infty} f_{A,B}(a,z-a) \mathrm da = \int_{-\infty}^{\infty} f_{A,B}(z-b,b) \mathrm ...
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1answer
29 views

How to obtain the convolution directly (not graphical) of the two functions $e^{-t}u(t)$ and $e^{-2t}u(t)$?

I'm having trouble solving this convolution integral graphically. I don't understand where I stop sliding my function $h(t-\lambda)$ since $x(t)$ doesn't have a boundary as lambda approaches infinity ...
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31 views

Equality condition for convolution's $L^p$ norm.

Suppose that $1< p< \infty$, $f\in L^1(R)$, and $g\in L^p(R)$ and that $\|f*g\|_p=\|f\|_1\|g\|_p$. Show that then either $f=0$ a.e or $g=0$ a.e I have solved for $g=0$ a.e. if $||f||_1>0$ ...
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44 views

convolve chirp with rect

I'm trying to evaluate $$g[x] = f[x] \ast f[x]$$ where * is the convolution operator and $$f[x] = RECT(\frac{x-2.5}{5}) \cdot exp (+i \pi x^2)$$ I assume the best approach to this equation is: ...
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22 views

estimate for derivative of convolution

Let $u\in L^\infty(\mathbb R\times (0,\infty))$ be a function such that $$u(x+z,t)-u(x,t)\leq c\left(1 + \frac 1 c\right)z\tag{$*$}$$ for some constant $c\in\mathbb R$ and almost all $x,z\in\mathbb ...
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1answer
17 views

what does support of convolution of functions says geometrically?

Let $f,g \in L^{1}(\mathbb R)$ we define $f\ast g(x)= \int_{\mathbb R} f(x-y)g(y) dy $ for all most all $x,$ and denote $\text{supp} (f)$ the support of $f.$ Fact: If $A$ is the closure of $\{x+y: ...
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1answer
22 views

convolution of non-zero functions

Let $f,g$ be two continuous functions with compact support. Show that if $f$ and $g$ are not identically $0$, then neither is $f\ast g$. This statement seems rather elementary, and I would prefer if ...
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29 views

Convolution of convex polygons and a Gaussian

I need to find the closest solutions for convolution of convex polygons/circles with a Gaussian function for computer graphics purposes. I was only able to find solutions for rectangles, like this ...
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2answers
46 views

Combining two convolution kernels

Is it possible to combine two convolution kernels (convolution in terms of image processing, so it's actually a correlation) into one, so that covnolving the image with the new kernel gives the same ...
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0answers
15 views

Convolution Theorem of a product of 3 functions of x

I am trying to evaluate the integral over a product of f(t), g(t) and h(t) using the convolution theorem. $$\int_0^\infty f(t) g(t)h(t) dt$$ So after taking the Laplace of each of f(t) g(t) & h(t) ...
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22 views

Lalplace Transform and Convolution theorem

How would one go about a problem of this nature $$\int_0^\infty f(t) g(t) dt$$ Using the convolution theorem. I have taken the Laplace transform of both f(t) and g(t) to get F(s) and G(s) however ...
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1answer
15 views

Deconvolution of two delta functions (solving $y(t) = A x(t-a) + B x(t-b)$)

I would like to calculate $x(t)$, when only $y(t)$ with $y(t) = A x(t-a) + B x(t-b)$ is known. Since this is a linear shift invariant operation (convolution), the inverse relation must be of the ...
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1answer
16 views

Using dirac delta functions to get $h(t)$ that satisfies $[u(t+1/2)-u(t-1/2)] \ast h(t) = [u(t+6)-u(t+2)]$ where $u(t)$ is unit-step function

Using dirac delta functions, how does one get $h(t)$ that satisfies $[u(t+1/2)-u(t-1/2)] \ast h(t) = [u(t+6)-u(t+2)]$ where $u(t)$ is unit(heaviside)-step function and $\ast$ is convolution?
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2answers
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convolution of $\delta(t+4) \ast \delta(t-1)$?

How does one solve convolution of $\delta(t+4) \ast \delta(t-1)$ where $\delta$ is dirac delta function? In ordinary function convolution, tricks are obvious but does dirac delta function share the ...
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1answer
136 views

Proof of Faà di Bruno's formula using a convolution identity for Bell polynomials?

I have noticed there is an identity for Bell polynomials that can apply of Faà di Bruno's formula. This is a convolution identity that states: $$ (x \ast y)_n = \sum_{j=1}^{n-1} {n \choose j} x_j ...
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1answer
24 views

Laplace transform convolution

$x(t) = cos(3πt)$ h(t) = $\exp(-2t)u(t)$ Find y(t) = x(t) * h(t) (ie convolution) Y(s) = X(s)H(s) and then take inverse laplace tranform of Y(s) $ L(x(t)) = \frac{s}{s^2+9π^2} $ $ L(h(t)) = ...
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1answer
27 views

Matlab: Impulse response of linear time invariable (LTI) sine-signal

I'm preparing for a lab in a Signals and Systems course in my university, 5th semester. I've found old exercise material from the class and since I know some Matlab and have dealt with LTI systems ...
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2answers
30 views

Convolution with delta function

I am merely looking for the result of the convolution of a function and a delta function. I know there is some sort of identity but I can't seem to find it. $\int_{-\infty}^{\infty} ...
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12 views

Calculating the probability mass function of the sum of two independent, non-similar, geometric random variables using convolution

Given two independent geometric random variables (where $p_1,p_2 \in [0,1]$): $$\mathbf{X_1} \sim \text{geometric}(p_1)$$ $$\mathbf{X_2} \sim \text{geometric}(p_2)$$ I want to find the probability ...
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28 views

Convolution of functions

If $f$ and $u$ are functions of $x$ defined in $(-\infty, \infty)$, then $f\ast u=\int f(x-t) u(t) dt $. But what is the result of $f \ast u_{xx}$?
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3answers
109 views

convolution of characteristic functions

Suppose $A$ and $B$ are measurable subsets of $\mathbb{R}$ of finite positive measure. Show that the convolution $\chi_A*\chi_B$ is continuous and not identically $0$. Use this to prove that $A+B$ ...
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1answer
28 views

Partial derivative of convolution

I have a convolution: $$g(x,\alpha) = \int_D \phi(t)f(x-t,\alpha)dt,$$ where $D$ is compact. I need to calculate $\frac{\partial}{\partial \alpha}g(x,\alpha)$. Under what conditions: ...
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23 views

If $\int^{s'}_{0} f(\gamma(s))ds\le g(s')$ is it true then that $\int^{s'}_{0} f_{n}(\gamma(s))ds\le g(s')$ for $f_{n}$ a convolution?

Let $f:\mathbb{R}^{n}\rightarrow \mathbb{R}$ be a $L^{2}$ function such that for any curve $\gamma:\mathbb{R}\rightarrow \mathbb{R}^{n}$ the following estimate is true $$\int^{s'}_{0} ...