Compressed Sampling for Neural Action Potentials Based on Random Convolution

Neurons Action Potentials (NAP) contain the most critical information of neurons actions. Based on the discussion for the sparsity characteristics of NAP presented in the DWT domain, and the analysis of related Compressive Sensing (CS) measurements, a compressed sampling method for NAP based on random convolution is proposed. For the aspects of the signal recovery and physical realization, three compression measurement methods are compared. The experiment results show compressed sampling method for NAP based on random convolution is the best compressed sampling scheme of the three for its system realization is simplest.