Endmember material identification for spectrum vector

I have some spectrum vector data that I collected from samples, and I want to identify the potential endmembers within the samples. I already have a list of potential endmember minerals and I was using USGS spectral library for those endmember. The collected spactral data were vectors with 2151 x 1. The USGS library also provide vector data with 2151 x 1.With the selected potential N end-member minerals. I was thinking about creating a matrix of 2151 x N and analysis with the samples' spectral vectors.

I tried to find the related function online but most of them were related to image unmixing process. I tink I need something similiar to the toolbox "Endmember Material Identification Using Spectral Library" (https://www.mathworks.com/help/images/end-member-material-identification-using-spectral-library.html), but instead of analysis an image, I'm looking for unmixing for individual spectral vector data.

It would be very nice if it is possible to have a result like: Sample 1 contains 60% of mineral A, 30% pf mineral B, and 5% of unknown material, based on spectrum unmixing. Does anybody heard about any function that could possibily support my analysis between vector and matrix? Thanks for any guidence or suggestion of starting points.