There is a growing consensus that solutions to complex science and engineering problems
require novel methodologies that are able to integrate traditional physics-based modeling …

Non-stationary time series (TS) analysis has gained an explosive interest over the recent
decades in different applied sciences. In fact, several decomposition methods were …

Patients with high-grade serous ovarian cancer suffer poor prognosis and variable response
to treatment. Known prognostic factors for this disease include homologous recombination …

The solution of a partial differential equation can be obtained by computing the inverse
operator map between the input and the solution space. Towards this end, we introduce a …

There is a growing consensus that solutions to complex science and engineering problems
require novel methodologies that are able to integrate traditional physics-based modeling …

Data-driven discovery is revolutionizing how we model, predict, and control complex
systems. Now with Python and MATLAB®, this textbook trains mathematical scientists and …

Epidemiology is the glorious discipline underlying medical research, public health practice,
and health care evaluation. Nowadays, research on disease models with anonymous …

In this paper, the operational matrix based on Bernstein wavelets is presented for solving
fractional SIR model with unknown parameters. The SIR model is a system of differential …

We consider linear inverse problems where the solution is assumed to have a sparse
expansion on an arbitrary preassigned orthonormal basis. We prove that replacing the usual …

Wavelet transforms are recent mathematical techniques, based on group theory and square
integrable representations, which allows one to unfold a signal, or a field, into both space …