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Batteries have been widely used in the field of electric vehicles. So prediction of the state of health (SOH) is important to the safe and efficient use of them. In this study, SOH is estimated by the generalized regression neural network (GRNN). GRNN is established by the radial basis neurons and linear neurons. The network has the advantages of approximation ability and the learning speed. In this...
A robust data-aided (DA) signal-to-noise ratio (SNR) estimation algorithm in the time domain is proposed in this paper, aiming at the volatile Doppler shift and carrier wave phase offset under dynamical scenarios for M-ary phase shift keying (MPSK) over the flat-fading complex channel. The proposed algorithm exploits data aided, delay conjugate multiplies the received signal, converts Doppler shift...
We propose a hierarchical regression approach, Dirichlet-tree cascaded Hough forests (DCHF), which is based on deep learning for continuous head pose estimation in unconstrained environment, e.g., poses, illumination, occlusion, low image resolution, expressions and make-up. First, positive facial patches are learned and extracted from facial area to eliminate the influence of noise. Then, in order...
To overcome the deficiencies of the existing methods used in the estimation of the crowd flow with high-density and multi-motion direction, a crowd flow estimation method based on dynamic texture and generalized regression neural network (GRNN) is presented in this paper. The method firstly extracts the dynamic texture features through optical flow, performs the moving crowd segmentation by the dynamic...
Accurate estimation of the State of Charge (SOC) of the battery is one of the key problems to the battery management system. The SOC should be obtained indirectly according to some algorithms under a mathematical model, along with some measurable quantities. A Sigma Point Kalman Filter based battery model parameters estimation method is proposed. The parameters can be estimated accurately while efficiently...
In an embedded system, the hardware resources are limited. In order to obtain such traffic information as traffic volume and vehicle speed in an embedded system, a series of efficient video processing algorithms and optimization techniques are proposed. The key algorithm to detect vehicles is the background subtraction method, in which the approximated median filter is applied to obtain the simulated...
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