By introducing some new terms, a novel piecewise time-dependent Lyapunov-Krasovskii functional (LKF) is constructed to fully capture the available characteristics of real sampling information and nonlinear function vector of the system.
It is suitable for small-sample learning and nonlinear and high dimension problem.
In this paper, we employ SVM [ 14], which are suitable for solving small-sample learning and nonlinear and high dimension problems, to establish the pancreatic cancer classification, and improve fruit fly optimization algorithm (FOA) [ 15] to optimize parameters of SVM.
As noted earlier, to examine the economic effects of defence spending in the case of the 13 Latin American countries of our sample, both linear and nonlinear causality tests will be employed.
This paper deals with the stabilization in the sample-and-hold sense of nonlinear, control affine, retarded systems, affected by actuation disturbances and observation errors.
Using these samples and both linear and nonlinear models, we identified tissue type-invariant DNAm age-associated signatures for both healthy normal and cancer samples.
It is due to its capability on classifying the samples by using linear and nonlinear separators.
The second part of the paper describes further recent developments of this reliable estimation technique, including its extension to handle coloured measurement noise situations, time-delay system identification, frequency-domain identification, non-uniformly sampled data, closed-loop and nonlinear model identification.
Let X = [ x 1, x 2, …, x M ] ∈ R K × M denote nonlinear samples and M the number of samples.
Table 3 shows the out-of-sample forecast results using linear and nonlinear time series methods.
