Multi-layer State Evolution Under Random Convolutional Design

Installation

To install the packages required to run this code, use the command conda create --name <env> --file Requirements.txt.

Running the Code

The code can be run using command line argument specied in main.py. See the documentation by running python main.py.

Here are some examples:

• For Figure 1, sparsity prior, with varying a (measurement ratio) and sparsity (average number of nonzero entries of prior samples):

python main.py --name Fig-1 --prior sparse --channel conv-cs --noise_std 0.01 -a {a} --sparsity {sparsity} --dims 1024 1024 3

• For Figure 5, ReLU prior, with varying a (measurement ratio) and L (number of layers of the prior):

python main.py --name Fig-5-ReLU --prior {L}-relu --channel cs --noise_std -0.01 -a {a} --dims 10000 10 3

• For Figure 5, Linear prior, with varying a (measurement ratio) and L (number of layers of the prior): :

python main.py --name Fig-5-Linear --prior {L}-relu --channel cs --noise_std -0.01 -a {a} --dims 10000 10 3

Note that including the --se flag will cause the code to run the state evolution simulation instead.