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A basis is proposed for identifying the stress within a structure, or within the critical part of a structure, which can be considered to govern both its overall and local deformations.
A subunit basis is proposed for channel opening and permeation in which these processes are coupled.
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In this paper, an efficient basis function expansion method based on wavelet multi-resolution analysis using cubic B-spline scaling functions as basis functions is proposed for identifying force history with high accuracy, which can overcome the deficiency of the ill-posed problem.
In this paper, a new computational method based on the generalized hat basis functions is proposed for solving stochastic Itô Volterra integral equations.
A collocation method based on multiquadric radial basis functions is proposed for numerical solution of fractional differential equations.
A fuzzy particle swarm optimization (PSO) on the basis of elite archiving is proposed for solving multi-objective optimization problems.
In this paper, an on-line learning neuro-control scheme that incorporates a growing radial basis function network (GRBFN) is proposed for a nonlinear aircraft controller design.
A multistep model predictive control (MPC) strategy based on dynamically recurrent radial basis function networks (RBFNs) is proposed for single-input single-output (SISO) control of uncertain nonlinear processes.
In this paper, an adaptive trajectory tracking controller based on extended normalized radial basis function network (ENRBFN) is proposed for 3-degree-of-freedom four rotor hover vehicle subjected to external disturbance i.e. wind turbulence.
A model constrained basis pursuit inversion method is proposed for stably estimating Young's modulus and Poisson's ratio.
By optimally allocating the power in different bands, a water-filling emission spectrum inspired by a novel conception of radius basis function neural-network is proposed for maximizing transmission energy efficiency in the presence of external interference.
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