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Recently, it has been proven [R. Soc. Open Sci. 1 (2014) 140124] that thecontinuous wavelet transform with non-admissible kernels (approximate wavelets)allows for an existence of the exact inverse transform. Here we consider thecomputational possibility for the realization of this approach. We providemodified simpler explanation of the reconstruction formula, restricted on thepractical case of real valued finite (or periodic/periodized) samples and thestandard (restricted) Morlet wavelet as a practically important example of anapproximate wavelet. The provided examples of applications includes the testfunction and the non-stationary electro-physical signals arising in the problemof neuroscience.

Computational implementation of the inverse continuous wavelet transform without a requirement of the admissibility condition