%Create the coefficient matrix. Store the coefficient matrix in A. A = [-2 1 2; 1 3 2; 3 -1 1] %Create the column matrix of constants. Store the column matrix of constants in b. b = [0; -4; 3] %Use ...

Abstract: The sparsity-regularized linear inverse problem has been widely used in many fields, such as remote sensing imaging, image processing and analysis, seismic deconvolution, compressed sensing, ...

You can create a release to package software, along with release notes and links to binary files, for other people to use. Learn more about releases in our docs.

Analog computers are systems that perform computations by manipulating physical quantities such as electrical current, that map math variables, instead of representing information using abstraction ...

Due to the complex behavior arising from non-uniqueness, symmetry, and bifurcations in the solution space, solving inverse problems of nonlinear differential equations (DEs) with multiple solutions is ...

Abstract: The system observability can be analyzed through calculating the rank of the system observability matrix. But the observability degree of each state of the system can't be expressed by this ...

Linear regression is the most fundamental machine learning technique to create a model that predicts a single numeric value. One of the three most common techniques to train a linear regression model ...