Hello Dr Quruat ul Ain:" Sparse representation has been applied in many domains, such as signal processing, image processing and machine learning. In this paper, a redundant dictionary with each column composed of a Voigt-like lineshape is constructed to represent the pure spectrum of the sample. With the prior knowledge that the baseline is smooth and sparse representation coefficient for a pure spectrum, a method simultaneously fitting the pure spectrum and baseline is proposed. Since the pure spectrum is nonnegative, the representation coefficients are also made to be nonnegative. Then through alternating optimization, a surrogate function based algorithm is used to obtain the sparse coefficients. "

Take a look at the following links:

Article Simultaneous spectrum fitting and baseline correction using ...

https://arxiv.org/pdf/1805.03695.pdf

Regards--

Ijaz Durrani Thank you for the answer. I will have a look