Ultrasonic guided waves have been extensively applied for non-destructive testing of plate-like structures particularly pipes in past two decades. In this regard, if a structure has a simple geometry, obtained guided waves' signals are easy to explain. However, any small degree of complexity in the geometry such as contacting with other materials may cause an extra amount of complication in the...

The operational challenge of a photovoltaic (PV) integrated system is the uncertainty (irregularity) future power output. integration and correct operation can be carried out with accurate forecasting PV output power. A distinct artificial intelligence method was employed in present study to forecast investigate accuracy using endogenous data. Discrete wavelet transforms were used decompose int...

Abstract In the present study, classical and proposed methods were used to investigate monthly precipitation characteristics of 30 stations in southeastern United States during 1968–2018. Maximal overlap discrete wavelet transform (MODWT) as preprocessing method K-means clustering used. First, time series decomposed into several subseries using MODWT considering db mother wavelet. Then, energy ...

Field seismic data can contain many sorts of noise and interferences. If the noise is stronger in order of magnitude than the signal, most techniques often applied in seismic processing will be severely affected. Denoising methods, even very robust schemes such as physical wavelet frame denoising (PWFD), are not exceptions. In this paper, we present a robust, data adaptive and fast 1D wavelet t...

We introduce a sparse image representation that takes advantage of the geometrical regularity of edges in images. A new class of one-dimensional wavelet orthonormal bases, called foveal wavelets, are introduced to detect and reconstruct singularities. Foveal wavelets are extended in two dimensions, to follow the geometry of arbitrary curves. The resulting two dimensional “bandelets” define orth...

Continuous wavelet design is the endeavor to construct mother wavelets with desirable properties for continuous transform (CWT). One class of methods choosing a involves minimizing functional, called uncertainty functional. Recently, two new functionals were derived from theoretical foundations. In both approaches, describes its concentration, or accuracy, as time-scale probe. While an can be p...

The trend of using deep learning techniques to classify arbitrary tasks has grown significantly in the last decade. Such background provide a stack non-linear functions solve that cannot be solved linear manner. Naturally, models can always almost any problem with right amount functional parameters. However, set preprocessing techniques, these might become much more accessible by negating need ...

Fetal phonocardiography (fPCG) based antenatal care system is economical and has a potential to use for long-term monitoring due to noninvasive nature of the system. The main limitation of this technique is that noise gets superimposed on the useful signal during its acquisition and transmission. Conventional filtering may result into loss of valuable diagnostic information from these signals. ...

Estimating sediment flow rate from a drainage area plays an essential role in better watershed planning and management. In this study, the validity of simple wavelet-coupled Artificial Intelligence (AI) models was analyzed for daily Suspended Sediment (SSC) estimation highly dynamic Koyna River basin India. Simple AI such as Neural Network (ANN) Adaptive Neuro-Fuzzy Inference System (ANFIS) wer...