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BP networks can be employed for linear non-separable pattern recognition, function fitting, and optimization.
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These methods are employed for linear fractional differential equations, and cannot be used for nonlinear equations.
Kalman Filters are employed for linear ones and a Modified Particle Filter for a nonlinear non-Gaussian subsystem which includes imperfect attitude rate dynamics is proposed.
The standard method based on the definition of the linear correlation function and the FFT procedure has frequently been employed for linear correlation and spectrum analyses.
The first approach is employed for linear methods in order to analyze and set up FPSE, which is based on the principle that the system is unstable or marginally stable [10].
A second objective was to compare the performance of four statistical modeling approaches that can be employed for binary classification: linear regression [ 10], logistic classification [ 11], and classification and regression trees (CART) [ 12, 13].
This class can be employed for computational solution of linear or non-linear functional equations, including ordinary differential equations or integral equations.
Different kernels were employed for SVM (Linear, Polynomial, Radial basis function and Sigmoid).
Kalman Filtering (KF) is employed for the linear and Gaussian subsystem consisting of angular velocity and drift dynamics together with gyroscope measurement.
Note that h ′ ( n ̂ k - 1 ) is employed for an approximated linear form using Taylor expansion due to the non-linearity of the state equation.
GPU acceleration is employed for dense and sparse linear algebra, while communication is minimized by a judicious data layout.
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