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How can I make transformations like:

sum(a*u[k]+b*v[k],k=1..n) into a*sum(u[k],k=1..n)+b*sum(v[k],k=1..n)

and in the opposite direction?

Dear all,

I have a question, why is the output of the inverse Laplace transformation if the signal is multiplied by itself not just convoluted in time domain:






The problem is how to plot a linear transformation, for example,


As, I searched, I found out that the code "LinearTransformPlot" can do that but it defines to act for example on lines or a certain subspace. May I ask you to learn the solution. Should we have a subspace untill we can plot the transformation? Thanks

Hi, there i want to basically plot the graph attached. It is basically the graph y= 2x^2 transformed to y = x^2. I can plot them, but how do they get the arrows showing the transformation and the arrows on the axis. Any help would be appreciated.


Maple gives the fourier transformation:

fourier(int(y^k*exp(-k*x*y/phi+I*y*omega), y = 0 .. infinity), omega, t) as:

2*Pi*t^k*exp(-t*k*x/phi)*piecewise(t < 0, 0, 1)+piecewise(0 < t, -2*Pi*t^k*exp(-t*k*x/phi), 0)

but it is identically 0.

if change the order of integration and integate exp(I*y*omega) first, the transform is equal to

int(Dirac(y-t)*y^k*exp(-k*x*y/phi), y = 0 .. infinity)

which is Heaviside(t)*t^k*exp(-t*k*x/phi)

With Maple I get the following result

A*x^`beta` = R-A*`beta`/(x^(1-`beta`)*(1-t))

For easier interpretation I would prefer the following, equivalent form:

1/(1-t) * 1/(R-A x^beta) = 1/(A*beta) * x^(1-beta)

I tryed a lot,...

Hello every one,

I am using similarity transformation to transform a PDE into an ODE.

I got the ode but its in a very ambiguous (unclear) form.

I need help to have the ode in a more friendly reading format.



I am trying to plot a graph in Maple on the (u,v) plane and I am struggling to work out how to do it.

Consider the change of variable

x=u^2-v^2                    y=2uv

Plot the lines in the (u,v) plane where x and y are constant.

If anybody could help  me in plotting this graph I would be very grateful.


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