Abstract: In this article, we propose a minimum simplex convolutional network (MiSiCNet) for deep hyperspectral unmixing. Unlike all the deep learning-based unmixing methods proposed in the literature ...

ABSTRACT: The purpose of this paper is to introduce a new pivot rule of the simplex algorithm. The simplex algorithm first presented by George B. Dantzig, is a widely used method for solving a linear ...

TSFitPy is a pipeline designed to determine stellar abundances and atmospheric parameters through the use of Nelder-Mead (simplex algorithm) minimization. It calculates model spectra "on the fly" ...

Solve linear programming problems using the Simplex method. Intuitive GUI for inputting objective functions and constraints. Visualize results and optimization steps.

The expectation-maximization algorithm maximises the likelihood function for problems involving latent or hidden variables. Latent variables are unobservable random variables that can introduce ...

Abstract: In this article, we introduce a deep learning-based technique for the linear hyperspectral unmixing problem. The proposed method contains two main steps. First, the endmembers are extracted ...

The purpose of this research paper is to introduce Easy Simplex Algorithm which is developed by author. The simplex algorithm first presented by G. B. Dantzing, is generally used for solving a Linear ...