How to use CompressedSensing package by using function instead of measurement matrix?


I am trying to use CompressedSensing package. I went through the examples in the documentation is as follows:

n=1000   #Signal Dimensions
m=400    #Measurement Dimension
k=100    #Approximate Sparsity

Signal = zeros(n)     #Create a random sparse signal
Signal[int(rand(k)*(n-1)+1)] = randn(k)

MM = randn(m,n)     #Create a random measurement matrix
Measurement = MM*Signal  #Measure the signal using the measurement matrix

#Reconstruct using IRLS
Reconstruction = IRLS(MM,Measurement,verbose=true)

I want to use a function instead of MM, because the size of MM will be very large in my case. Then my code will be modified as

Measurement = measurement_function(Signal)  #Measure the signal using the measurement function

Then I want to use that function for reconstruction of signal, something look like below:

Reconstruction = IRLS(measurement_function(),Measurement)

Will it be possible with CompressedSensing package?

Thanks in Advance!

Are you talking about this package?

It appears to have been archived and not updated for 5 years.

1 Like

@baggepinnen : yes …I tried to use this… ohh it’s archived … :pensive: Sorry to disturb you