Abstract
A new method for deconvoluting data with statistical noise and sharp spike in the actual profile has been developed. It is applicable to a kernel of the general form and it allows to reveal some structure information which was not visible in the original data signal. The unknown function is assumed to be a superposition of a delta function and cubic splines. It is well adapted to the measurement of depth profiling of elements in matter by means of nuclear microanalysis.
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