We give a brief review of some of the wavelet-based techniques currently available for the analysis of arbitrary-length discrete time series. We discuss the maximal overlap discrete wavelet packet transform (MODWPT), a non-decimated version of the usual discrete wavelet packet transform, and a special case, the maximal overlap discrete wavelet transform (MODWT). Using least-asymmetric or coifle...

Many surveillance and forensic applications face problems in identifying shadows and their removal. The moving shadow points overlap with the moving objects in a video sequence leading to misclassification of the exact object. This article presents a novel method for identifying and removing moving shadows using stationary wavelet transform (SWT) based on a threshold determined by wavelet coeff...

Spikes are short-time broadband events, which can last 20ms-70ms and amplitude is among 100?V-200?V. In this research, a novel spike detection method based on stationary wavelet transform (SWT) and time-varying autoregressive model is proposed. In the proposed method, the discrete stationary wavelet transform is initially applied on the signal under analysis to show the important underlying una...

In analyzing a signal, especially a non-stationary signal, it is often necessary the desired signal to be segmented into small epochs. Segmentation can be performed by splitting the signal at time instances where signal amplitude or frequency change. In this paper, the signal is initially decomposed into signals with different frequency bands using wavelet transform. Then, fractal dimension of ...

The process of calculating the effective values of voltage and current root mean square (RMS) using Fourier transform (FT) suffers a high computational effort. Since it provides only an amplitude-frequency spectrum, looses time-related information, and is unable to deal with no stationary waveforms, standard definitions are reformulated in the time-frequency domain using the wavelet transform (...

Air quality measurements and forecasting is one of the most popular research topics in field sustainable intelligent environmental design, urban area development pollution control, especially for Asia developing countries, such as China. Deep learning (DL) technologies time series data forecasting, recurrent neural network (RNN) long short term memory (LSTM) network, have attracted extensive at...

This work is based on the comparative study of different decomposition methods used to de-noise an ECG signal. There are several signal processing techniques available like Fourier Transform method, Short Term Fourier Transform method, Wavelet analysis, Empirical Mode of Decomposition method etc. Though Fourier Transform method is predominantly used for decomposition purpose but it is not suita...