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We propose a scheme for maintaining the requested SIR of each user under uncertainty of system parameters in the power control of interference limited wireless networks. In doing so, we keep the outage probability of users below their predefined threshold with minimal power consumption. To reduce the complexity, we apply the notion of chance constraint robust optimization to the outage probability...
In this paper, a novel algorithm called Receding Horizon Kalman Particle Filter (RHKPF) has been proposed and is applied to our improved fingerprint-based WLAN vehicle positioning system. The RHKPF is a particle filter that the optimal importance density is approximated by incorporating the most current measurement through a Receding Horizon Kalman Filter (RHKF), for that the RHKF is believed to be...
The normalized least-mean-fourth (XE-NLMF) algorithm has a faster convergence rate and lower misalignment performance than the normalized least-mean-squares (NLMS) algorithm in sub-Gaussian noise environments. However, the XE-NLMF algorithm shows convergence performance degradation in highly correlated input signals. To overcome the problem, we propose an XE-NLMF algorithm with variable data-reusing...
Noise often leads to bad generalization of network. Many of the typical algorithms can not be applied for the on-line identification of complex system since they are not robust to the variance of the energy of noise. A new algorithm is proposed to solve this problem based on the frequency band of wavelet network. It is shown that the wavelet network trained by the new algorithm is a low-pass filter,...
As inspired by revising (Zhang and Ge, 2003), the traditional gradient-based neural system (also termed analog computer (Manherz et al., 1968)) for matrix inversion is re-visited by examining different activation functions and various implementation errors. A general neural system for matrix inversion is thus presented which can be constructed by using monotonically-increasing odd activation functions...
A new identification concept is offered in this paper, and it is shown how to identify the unknown parameters of nonlinear flight dynamic systems assuming that a generic nonlinear model is known. To ensure robustness and parameter convergence, nonlinear error mappings are used, and the Lyapunov second method is employed to approach the analysis of convergence. The explored method is applied to a longitudinal...
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