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Parsing urban scene images benefits many applications, especially self-driving. Most of the current solutions employ generic image parsing models that treat all scales and locations in the images equally and do not consider the geometry property of car-captured urban scene images. Thus, they suffer from heterogeneous object scales caused by perspective projection of cameras on actual scenes and inevitably...
In this paper, a universal control scheme is investigated for a class of nonlinear systems with unknown parameters and nonlinearities like friction, dead-zone, etc. First of all, an adaptive finite-time update law is developed to estimate the unknown parameters by introducing the auxiliary filtered variables for the system states and regressor matrix. Then, a universal controller is proposed based...
In order to remove desired signal component from the sample covariance matrix, a novel robust adaptive beamformer is proposed based on desired signal covariance matrix estimation. The desired signal direction is first calculated based on the first-order Taylor series approximation, and then the desired signal's steering vector and power are estimated by using iterative robust minimum variance beamforming,...
This paper addresses the issue of UWB signal acquisition in the context of wireless powered UWB RFID systems. In this scenario, the data transmission is based on short packet so as to meet the micro-power budget of autonomous power harvesting. The burst short packet transmission as well as the low duty cycling UWB pulse modulation places a stringent challenge at the UWB receiver for timing acquisition...
A hybrid approach using the sampled pattern matching (SPM) method and matrix inversion is utilized to estimate current distribution of electromagnetic radiation sources with multi-mode current distribution. The current distribution of a loop antenna is detected as an example. The capability of the hybrid method in handling practical problems is demonstrated by estimating the amplitude and phase of...
This paper presents a new energy minimization method for simultaneous image segmentation and bias field estimation of magnetic resonance (MR) images. The proposed algorithm introduces the global intensity into the algorithm CLIC and combines the local and global intensity information into account. The segmentation target therefore is driven by two forces, one induced by the coherent local intensity...
In this paper a system level analysis and implementation of two-layer mobile wireless sensor network architecture is proposed for tracking and environmental supervision applications. It uses a mobile Master Sensor Node (MSN) that collects information inside a Sensor Area Network (SAN) where many semi-passive Slave Sensor Nodes (SSN) are deployed. The collected information is sent through a Wireless...
In practice, nonnegative data factorization is often performed for data dimensionality reduction prior to a classification task using a classifier which is effective in low dimensional space such as nearest neighbor classifier. In this work, we propose a novel formulation to learn a multi-class classifier directly through a supervised nonnegative data factorization. This new formulation has the following...
Approaches to estimate the current distribution on EM source such as antennas and printed circuit board (PCB) by measuring the near-field distribution are demonstrated. These approaches include the matrix inversion method and sampled pattern matching (SPM) method. All of these approaches require accurate near-field measurement and field-current inverse algorithm. Experimental results are presented...
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