Defect Detection by Split Spectrum Processing and Discrete Wavelet Transform in Coarse Grains Materials

The construction, using the group algebra of an abelian group and a special partition or splitting of the group, yields quadratic residue codes, duadic codes, and their

The results of a previous study [39] using a visual search task revealed that preschool children detected a snake image among flower images faster when the images were in color

More precisely, he says the following: there exists non-real eigenvalues of singular indefinite Sturm-Liouville operators accumulate to the real axis whenever the eigenvalues of

In this paper, some signal processing algoritms mike split spectrum processing (SSP) and wavelets are developed and implemented on computer allowing their utilization in ultrasonics

The grain noise signal is generated first, by a simple clutter model which consider the noise, in the time domain, as the superimposed of signal coming

Abstract : In this work, we propose in one hand, to develop algorithms based on Split Spectrum Processing (SSP) with Q constant method associated to "Group delay moving

In this context, we develop signal processing tools based on Split Spectrum Processing (SSP) with Q constant method allowing to detect and locate the imperfections present in

So, we show that theapplication of algorithms based on Split Spectrum Processing (SSP) and the Discrete Wavelet transform (DWT), can increase detection possibilities.. A