This paper proposes a speech signal enhancement method in which the wavelet transform scales and thresholds both are adaptive depending on the input noisy signal affected by Additive White Gaussian Noise (AWGN). The proposed Estimated Noise and Adaptive Threshold Bionic Wavelet Transform (ENAT-BWT) method analyses the incoming noisy speech signal at 22 scales, from 7 to 28, of the BWT for negat...

We present an algorithm for denoising of videos corrupted by additive i.i.d. zero mean Gaussian noise with a fixed and known standard deviation. Our algorithm is patch-based. Given a patch from a frame in the video, the algorithm collects similar patches from the same and adjacent frames. All the patches in this group are denoised using a transform-based approach that involves hard thresholding...

In this paper, a novel method for the classification of power quality events is illustrated. Fifteen types consisting single and multi-stage disturbances are considered study. A database synthetic PQ generated in MATLAB using mathematical models. The signals passed through modified Stockwell transform second-order Gaussian window that provides ST matrix. From matrix, various statistical feature...

We address the problem of modelling asymmetric pulses within the framework of finite-rate-of-innovation (FRI) signals. We use the fractional Hilbert transform to model asymmetry in the pulse shape. The annihilating filter is employed to estimate the locations of the pulses. The asymmetry of the pulses manifests as a complex phase factor in the Fourierdomain expression of the signal. We model a ...

The S transform is variable window of short time Fourier transform (STFT) or an extension of wavelet transform (WT). It is based on a scalable localizing Gaussian window and supplies the frequency dependent resolution. In this tutorial, we introduce the fundamental function of S transform and the generalized S transform. Furthermore, we present some applications of S transform: seismogram analy...