We have designed an adaptive essentially nonoscillatory (ENO)-wavelet transform for approximating discontinuous functions without oscillations near the discontinuities. Our approach is to apply the ...

This paper introduces new protocols for secure multiparty computation (MPC) leveraging Discrete Wavelet Transforms (DWTs) for computing nonlinear functions over large domains. By employing DWTs, the ...

Fault detection in a distribution network using a combination of a discrete wavelet transform and a neural Network’s radial basis function algorithm to detect high-impedance faults ...

The relevance of developing new algorithms for diagnosing cardiovascular diseases is due to the fact that these diseases are the leading cause of death worldwide. One form of potential disease is an ...

Single image dehazing is the ill-posed two-dimensional signal reconstruction problem. Recently, deep convolutional neural networks (CNN) have been successfully used in many computer vision problems.

The transform is similar to applying Fourier, but instead of decomposing to a series of infinite sine waves, wavelet transformation decomposes signals into finite functions that meet certain ...

Eric D. Kolaczyk, Wavelet-Based Nonparametric Modeling of Hierarchical Functions in Colon Carcinogenesis [with Comment], Journal of the American Statistical Association, Vol. 98, No. 463 (Sep., 2003), ...