In this paper we show that Compressive Sensing (CS) can be casted as an impulse response estimation problem. Using this interpretation we re-obtain some theoretical results of CS in a simple manner. Moreover, we prove that in the case of a randomly generated sensing matrix, reconstruction probability depends on the kurtosis of the distribution used for its generation.