Sentence examples for finite number of data from inspiring English sources

The proposed technique aims to learn the behavior of a human pilot, by exploiting a finite number of data collected during manual operation of the system, hence avoiding the need for an explicit model of the system dynamics.

By estimating the joint probability density function (pdf) of Equation (7) by the Parzen method from a finite number of data { ( x i, y i ) } i = 1 n, the right-hand side of Equation (6) is obtained v ^ σ ( X, Y ) = 1 n ∑ i = 1 n G σ 2 ( x i − y i ).

The obtained confidence region is valid for finite numbers of data points when the distributions of the observations are unknown.

A transient inverse heat conduction analysis enables the identification of the unknown boundary heat flux from finite number of temperature data obtained, e.g., in the high temperature structural tests or in the actual operation.

Artificial neural network (ANN) is a stochastic and heuristic tool that learns the relationship between the parameters and their responses when trained with a finite number of input data and predicts the values of response from the new set of independent variables based on its training experience.

Inadequate number of training samples for the finite number of training data leads to "curse of dimensionality" problem, which leads to degraded classification performance [43,44].

The CRs utilize finite number of received data samples for estimating the energy of the primary signals and forward these energy estimates to a fusion center (FC).

In general, as it is assumed that internal-combustion engines are highly nonlinear systems, it is impossible to exactly represent the AOD of the automotive engine from a finite number of acquired data.

Should a questionnaire generate only a finite number of scores, the data will then be considered polytomous and suitable statistical techniques will be used to analyse any such data.

It is also shown that the designed estimators are optimal, in the sense that they give minimal worst-case estimation error, on the basis of the available finite number of noise-corrupted data, with respect to an ideal MHE filter (obtained by assuming exact knowledge of the system dynamics and of the global solution of the related nonlinear program).

In this paper, we have demonstrated that it is possible for a collaborative cognitive radio network to detect the spectrum hole in an optimal manner by minimizing the total probability of error in decision making with a finite number of the received data samples.