Sentence examples for linear transformation method from inspiring English sources

The second method we introduce is the linear transformation method.

In addition, the linear transformation method can also be generalized into stochastic cases.

The linear transformation method generalizes the application scope of monotonicity conditions.

In order to classify and quantify these variations, linear transformation method of PCA was first applied.

In the next section, the linear transformation method is used to generalize the framework of the monotonicity conditions.

This study first presented an investigation of the time series method, linear transformation method and Johnson transformation system.

Well-known linear transformation methods include principal component analysis, factor analysis, and projection pursuit.

In Section 5.1 we summarize certain stochastic and geometric representations and linear transformation methods from (Richter 2014; 2015a) and (Richter and Schicker 2017) for the particular classes of convex polyhedra and polyhedral convex contoured distributions, respectively.

(A), (B): scenario 1; (C), (D): scenario 2. After selecting the most relevant variables, the data set obtained (comprising the most relevant variables) was further reduced using the linear transformation methods commented before.

The method directly deals with highly redundant and irrelevant data contained in the bi-dimensional t f representations, combining a first stage of irrelevant data removal by variable selection using a relevance measure, with a second stage of redundancy reduction by linear transformation methods.

Moreover, an optimized modified direct linear transformation (MDLT) method has been used to reconstruct 3D markers positions which are used for deriving kinematic characteristics of the motion.