Transform matrix creation in compressed sensing In Compressed sensing ECG reconstruction I would like to use biorthogonal wavelet basis as transform/sparsifying domain. I found out that wfilters command in MATLAB will give 4 type of filters, but which filter I would use to make the transform matrix? 

Either decomposition lowpass/highpass or reconstruction low pass/high pass or is there any other better ways to make the transform matrix??
I recommend not forming the transform matrix directly. That will cost more memory and take longer to compute the transform. Instead, use the idwt/dwt or waverec/wavedec functions in place of multiplying by A/A.T.
Many reconstruction solvers and convex optimisation toolboxes support supplying function handles for this instead of a matrix. If you are implementing your own solver it should also be easy enough to integrate these functions instead of the matrix-vector products.