Energy of compressed signals I have tried a code to compress a signal using Compressed Sensing(CS).
  The input signal is $x$ and the compressed signal  $y$ is given by :
 $y=Φ*x$   where $Φ$ is the sensing matrix.
I have used the following matlab function to compute the energy of $x$ and the energy of $y$ .


  energy_x= sum(x(1:384,:).^2);
  energy_y = sum(y(1:192,:).^2);


The length of $x$ is 384 , and the length of $y$ is 192.
I found that the energy of $x$ is 446910
  and the energy of $y$ is 77651282 .
Is it is reasonable to obtain higher energy for the output than the input?
Without information on  $Φ$, you can obtain almost anything, since $\lambda Φ$ could be a valid CS matrix as well. Generally, one imposes structure contraints, such as unit energy for their rows or columns.

This being said, compressive sensing does not compress data in a strict sense, and energy is a poor measure of compressibility. Entropy and norm ratios could be more interesting measures.