two multivariate calibration methods are compared for the simultaneous chromatographic determination and separation of sulfamethoxazole (smx) and phthalazine (phz) by high performance liquid chromatography (hplc). multivariate calibration techniques such as classical least squares (cls) and inverse least squares (ils) were introduced into hplc to determine the quantification by using uv detecto...

For fast detection of inorganic phosphorus fractions and their phosphorus contents in soil, a method employing near-infrared spectroscopy (NIRS) combined with partial least squares (PLS) and least squares support vector machine (LS-SVM) was proposed. Fifty soil samples for each of iron phosphate, magnesium phosphate, calcium phosphate and aluminum phosphate, with application rates of phosphate ...

io-port 06474690 Laurain, Vincent; Tóth, Roland; Piga, Dario; Zheng, Wei Xing An instrumental least squares support vector machine for nonlinear system identification. Automatica 54, Article ID 6308, 340-347 (2015). Summary: Least-Squares Support Vector Machines (LS-SVMs), originating from Statistical Learning and Reproducing Kernel Hilbert Space (RKHS) theories, represent a promising approach ...

The standard approaches to solving overdetermined linear systems Bx ≈ c construct minimal corrections to the data to make the corrected system compatible. In ordinary least squares (LS) the correction is restricted to the right hand side c, while in scaled total least squares (STLS) [14, 12] corrections to both c and B are allowed, and their relative sizes are determined by a real positive para...

Among Neural Network methods, the Support Vector Machine (SVM) solutions are attracting increasing attention, mostly because they automatically derive the “optimal” network structure, in respect to generalization error for a given problem. In practice it means, that a lot of decisions that had to be made during the design of a traditional NN (e.g. the number of neurons, the length and type of t...

In this paper, we first get further consideration of the order perturbation with normwise condition number MTLS problem. For easy estimation, show a lower bound for which is proved to be optimal. overcome problems encountered in calculating number, give an upper computing more effectively and nonstandard unusual bounds Both two types can enjoy storage computational advantages. getting insight i...

The standard approaches to solving overdetermined linear systems Bx ≈ c construct minimal corrections to the vector c and/or the matrix B such that the corrected system is compatible. In ordinary least squares (LS) the correction is restricted to c, while in data least squares (DLS) it is restricted to B. In scaled total least squares (STLS) [22], corrections to both c and B are allowed, and th...

Building a calibration model with detection and quantification capabilities is identical to the task of building a regression model. Although commonly used by analysts, an application of the calibration model requires at first careful attention to the three components of the regression triplet (data, model, method), examining (a) the data quality of the proposed model; (b) the model quality; (c...

In this work, we developed classifiers to distinguish between four ovarian tumor types using Bayesian least squares support vector machines (LS-SVMs) and kernel logistic regression. Input selection using rank-one updates for LS-SVMs performed better than automatic relevance determination. Evaluation on an independent test set showed good performance of the classifiers to distinguish between all...