ill-conditioned
11Numerical analysis — Babylonian clay tablet BC 7289 (c. 1800–1600 BC) with annotations. The approximation of the square root of 2 is four sexagesimal figures, which is about six decimal figures. 1 + 24/60 + 51/602 + 10/603 = 1.41421296...[1] Numerical analysis is the …
12Linear least squares — is an important computational problem, that arises primarily in applications when it is desired to fit a linear mathematical model to measurements obtained from experiments. The goals of linear least squares are to extract predictions from the… …
13Linear least squares/Proposed — Linear least squares is an important computational problem, that arises primarily in applications when it is desired to fit a linear mathematical model to observations obtained from experiments. Mathematically, it can be stated as the problem of… …
14Linear least squares (mathematics) — This article is about the mathematics that underlie curve fitting using linear least squares. For statistical regression analysis using least squares, see linear regression. For linear regression on a single variable, see simple linear regression …
15Well-posed problem — The mathematical term well posed problem stems from a definition given by Hadamard. He believed that mathematical models of physical phenomena should have the properties that # A solution exists # The solution is unique # The solution depends… …
16Kahan summation algorithm — In numerical analysis, the Kahan summation algorithm (also known as compensated summation) significantly reduces the numerical error in the total obtained by adding a sequence of finite precision floating point numbers, compared to the obvious… …
17Tikhonov regularization — Tikhonov regularization, named for Andrey Tikhonov, is the most commonly used method of regularization of ill posed problems. In statistics, the method is known as ridge regression, and, with multiple independent discoveries, it is also variously …
18CMA-ES — stands for Covariance Matrix Adaptation Evolution Strategy. Evolution strategies (ES) are stochastic, derivative free methods for numerical optimization of non linear or non convex continuous optimization problems. They belong to the class of… …
19Inverse problem — An inverse problem is a general framework that is used to convert observed measurements into information about a physical object or system that we are interested in. For example, if we have measurements of the Earth s gravity field, then we might …
20Malevolence — (Roget s Thesaurus) < N PARAG:Malevolence >N GRP: N 1 Sgm: N 1 malevolence malevolence Sgm: N 1 bad intent bad intent bad intention Sgm: N 1 unkindness unkindness diskindness Sgm: N 1 ill nature ill nature ill will ill blood …
