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This paper deals with the cooperative control problem for second-order agents formation circling along meridian and parallel on a given sphere centered at a target of interest, where the direction of the target's movement is known to each agent but the target's speed is unknown. By using local measurements of relative position, a novel distributed solution is proposed by separatively designing each...
Different from representation learning models using deep learning to project original feature space into lower density ones, we propose a feature space learning (FSL) model based on a semi-supervised clustering framework. There are three main contributions in our approach: (1) Inspired by Zipf's law and word bursts, the feature space learning processes not only select trusted unlabeled samples and...
In this paper we propose a compressive channel estimation for fast fading channel in orthogonal frequency division multiplexing (OFDM) systems. We formulate the sparse compressive sensing (CS) problem by exploiting the delay-Doppler sparse structure of the doubly dispersive channel. To combat the severe inter-carrier interference (ICI) caused by the Doppler shift, this estimator is based on the banded...
Remaining Useful Life (RUL) prediction plays a critical part in many battery-powered applications. Statistical filter, i.e., particle filter (PF) is widely used to predict RUL with various models as well as its uncertainty representation. However, PF commonly used suffers from the lack of poor adaption of long-term prediction and iterative prediction. This disadvantage may further reduce the RUL estimation...
Lithium-ion battery remaining useful life (RUL) estimation has become a critical issue of intelligent battery management system (BMS). Various models and algorithms have been developed to achieve the RUL prognostics for lithium-ion batteries, to obtain high estimation performance. Generally, a single model usually requires long train time and complex train progress to reach satisfactory precision,...
Inverse Truncated Mixing Matrix (ITMM) is a powerful method for underdetermined instantaneous blind source separation [1]. In this paper, we generalize ITMM algorithm to underdetermined convolutive blind source separation case. The proposed algorithm can be divided into two steps. The first step is the mixing filters estimation. The convolutive mixture can become an instantaneous mixture in time-frequency...
The hybrid filter bank (HFB) A/D converters permits implementing both high speed and high resolution A/D converters. However, its design requires an accurate knowledge of the analog filter bank coefficients, which is difficult to have due to analog imperfections. This paper proposes an adaptive blind equalization method for MIMO HFB A/D converters, which is able to adaptively estimate nonstationary...
According to the Root-MUSIC algorithm for acoustic pressure sensor array, we put forward a new Root-MUSIC algorithm with real-valued eigendecomposition for acoustic vector sensor array,. By way of recomposing the covariance matrix of vector sensor array and selecting appropriate lead orientation vector via spatial spectrum of array signal, we successfully evaluate the Direction of Arriva (DOA). Theory...
Studying drivers' route choice behavior under the influence of travel information is important because it provides insight to improve the effect of travel information on traffic environment. This paper mainly aims to study the impact of travel information on travelers' route choice behavior at different departure time. Multinomial logit model (MNL) is used to model travelers' route choice behavior...
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