Given an n x n square matrix A, if there exists another matrix B such that AB = BA = I (where I is the identity matrix), then B is called the inverse matrix of A and is denoted by A-1. The general ...
Numerical-Methods-Project/ │ ├── README.md │ ├── 01_Solution_of_Linear_Equations/ │ │ │ ├── Gauss_Elimination/ │ │ ├── theory.md ...
Kernel ridge regression (KRR) is a regression technique for predicting a single numeric value and can deliver high accuracy for complex, non-linear data. KRR combines a kernel function (most commonly ...
Abstract: An efficient, accurate, and robust inversion algorithm is proposed in this work to reconstruct perfect electric conductor (PEC) scatterers, which considers the complex multiple scattering ...
Matrix factorization techniques, such as principal component analysis (PCA) and independent component analysis (ICA), are widely used to extract geological processes from geochemical data. However, ...
Stochastic inversion method based on compressed sensing frequency division waveform indication prior
The stochastic inversion method using logging data as conditional data and seismic data as constraint data has a higher vertical resolution than the conventional deterministic inversion method.
Abstract: An improved variant of the precise-integration time-domain (PITD) method is proposed to eliminate the inverse matrix calculation and optimize the storage burden with the help of sparse ...
Erasures codes, particularly those protecting against multiple failures in RAID disk arrays, provide a code-specific means for reconstruction of lost (erased) data. In the RAID application this is ...
Researchers claim to have developed a new way to run AI language models more efficiently by eliminating matrix multiplication from the process. This fundamentally redesigns neural network operations ...
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