Bernoulli sensing matrix for compressed sensing using matlab
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I am trying to implement compressed sensing in matlab, also trying different types of sensing matrix (Gaussian, Bernoulli, Fourier), and I have problems implementing -+1 Bernoulli random matrix as a sensing matrix, I am generating it as follows:
p=0.5;
A=(rand(M,256)<p);
A=A*2-1;
where M is
M => C*K*log(N/K)
N is the vector length, K is the non-zero coefficients, is that correct?
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Walter Roberson
2015-10-7
Your M does not appear to be restricted to non-negative integers, which would be required to use as the number of rows for rand()
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2015-10-7
2015-10-7
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