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An adaptive handover algorithm for wireless communication systems is addressed in this paper. Moving from the Generalized Extended Least Square handover algorithm proposed in, we model the handover mechanism as a hybrid system, and we include it in a dynamic optimization problem which is solved through the use of a trellis diagram. It's the key segment in moving Least-Square Approximation that computing...
A Mesic respiratory system parameter identification is studied in this paper for providing the useful theory and data support in the improvement of human respiratory model accuracy, respiratory disease diagnosis and design of the new ventilator. The Mesic respiratory system model is established based on Simulink platform. The least-square algorithm is then used to do the static and dynamic parameter...
In this paper, we present an FPGA implementation of a Recursive Least Squares adaptive filtering algorithm based on dichotomous coordinate descent iterations. The algorithm is simple for finite precision implementation, requires small chip resources, and exhibits numerical stability. For arbitrary regressors (as in antenna array beamforming), the proposed implementation allows significant increase...
A method for simultaneous localization and mapping based on scan matching is presented according to memory database of the features. The steady geometric features are extracted as the natural landmarks according to advanced least square fitting, and the memory database of the features is created and updated for scan matching better. Therefore, it is also adapted to dynamic environment. Meanwhile,...
The recursive least squares (RLS) adaptive filtering problem is expressed in terms of auxiliary normal equations with respect to increments of the filter weights. By applying this approach to the exponentially weighted case, a new structure of the RLS algorithm is derived. For solving the auxiliary equations, dichotomous coordinate descent (DCD) iterations with no explicit division and multiplication...
Superheater steam temperature in power plant is the strong nonlinearity system. Sparse Least squares support vector networks (LSSVN) are proposed to model the superheated steam of power plant in this paper. The structure is obtained by equality constrained minimization. By combining the DMC with discount recursive partial least squares (DRPLS), a adaptive DMC control method based on discount recursive...
Super-heater steam temperature in power plant is the strong nonlinearity system. Though neural networks have the ability to approximate nonlinear functions with arbitrary accuracy, good generalization results are obtained only if the structure of the network is suitably chosen. Therefore, selecting the "best" structure of the neural network is more difficulty. Sparse least squares support...
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