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Rain streaks removal from single image is a challenging problem for image processing. This paper proposed a novel algorithm for rain streaks removal to single image based on a self-learning framework and structured sparse representation. More precisely, our algorithm firstly segments and categorizes input image into “rain streaks” regions and “non-rain geometric” regions via texture analysis. Meanwhile,...
In this paper, we propose an image-based collision detection optimization algorithm in order to meet the high requirements of real-time and accuracy in the increasingly complex collision detection environment. The algorithm can deal with arbitrary model and will make efficient use of the GPU on the basis of RECODE and RAPID algorithm. In this paper, the algorithm flow will be divided into two stages:...
Frequency Diverse Array (FDA) can provide range-angle-dependent beam which is different from the angle-only directional beam of conventional phased-array and bring potential applications. Small frequency offset between adjacent elements is the essential difference compared with conventional phased-array. In this paper, we propose two transmit beampattern synthesis schemes for linear FDA to focus transmit...
The subjective Chinese speech intelligibility evaluation experiments and objective speech transmission index STIPA measurements were respectively carried out under a total of 234 simulated transmission conditions. The relationship curve between Chinese intelligibility scores and STIPA was established and compared with the standard reference curves given in IEC 60268-16 2011. It is found that remarkable...
This paper investigates the formation of ad-hoc microphone arrays for the purpose of recording multiple sound sources by clustering microphones spatially distributed within a room. A novel codebook-based unsupervised method for cluster formation using features derived from the Room Impulse Responses (RIRs) corresponding to each microphone is proposed and compared with baseline clustering and classification...
In active noise control (ANC) system, the injection of white Gaussian noise (WGN) for online feedback path modeling and neutralization (FBPMN) degrades the noise-reduction-performance (NRP). In this paper: (1) a tuning free gain scheduling of WGN is used to improve the NRP of ANC system, and (2) a variable step-size is used to compensate for the decrease in the convergence of FBPMN filter due to gain...
Peak-to-average power ratio (PAPR) reduction of OFDM signal has been a subject of intense research in the last decade. In this paper, we propose an undistorted PAPR reduction method for OFDM systems, which combines the Interleaving Method and a modified Partial Transmit Sequence (PTS) method with the new phase rotation. The computational complexity of Interleaving Method is lower, compared with PTS...
Joint precoding for multiple-input multiple-output (MIMO) two-way relay networks has recently received much attention. In this paper, we present a coherent way to iteratively optimize the source and relay precoding matrices based on convex programming. Although the proposed total mean-square error (MSE) minimization problem is not joint convex for both the sources and relay, the subproblems for separate...
Signal estimation in MIMO communications typically suffers from performance degradations due to imperfect channel state information (CSI). Traditional robustification schemes rely on assumptions about the model uncertainty and may result in conservative performance. We introduce a rank-reduction approach that enhances the performance in training-based applications. A sequence of reduced-rank channel...
We propose a novel Bayesian compressive sensing reconstruction algorithm based on the context modeling of intra-scale wavelet coefficients, which utilizes the statistical dependencies in different directions. We assume that the wavelet coefficients obey a spike-and-slab probability model, whose parameters can be estimated according to a novel context-based model. In the context-based model, 3×3, 5×5...
To alleviate the adverse effect of the multipath fading, we need to estimate the required fading margin for the link budget analysis. Compared with the Monte Carlo simulations, the theoretical analysis can estimate the system performance more rapidly and precisely. This paper studies the outage performance for selection combining based on the generalized correlated Weibull distribution with arbitrary...
In this paper, a Bayesian dynamic model is proposed to evaluate the sensor nodes' credibilities online, in a paradigm of agricultural Internet of things (IoT). The purpose is to discriminate reliable and unreliable data items before further data analysis, and thus to implement reliable data analysis. The credibility of the sensor node of interest is treated as the state variable of the model. The...
Research on non-intrusive speech quality assessment (SQA) aims to develop a computational model simulating the human perception of speech signals accurately and automatically without any prior information about the reference clean speech signals. In this paper, we propose to learn a non-intrusive SQA metric based on bag-of-words (BoW) representation of speech signals. In particular, the proposed method...
This work proposes a novel reversible visible watermarking scheme for encrypted images. In the scheme, the original plaintext image is encrypted by bit-wise exclusive-or operation. Although a data-hider does not know the original content, he may modify a part of encrypted data corresponding to the black pixels of a binary watermark image to insert the visible watermark. Meanwhile, some additional...
The tracking of moving biological cells in time-lapse video sequences is fundamental to further understanding biological processes. Automatic cell tracking techniques require accurate cell image segmentation; however, current segmentation techniques are susceptible to errors due to non-ideal but realistic cell image conditions, including low contrast typical of cell microscopic images. This paper...
A new policy-iteration algorithm based on neural networks (NNs) is proposed in this paper to synthesize optimal control laws online for continuous-time nonlinear systems. Latest advances in this field have enabled synchronous policy iteration but require an additional tuning loop or a logic switch mechanism to maintain system stability. A new algorithm is thus derived in this paper to address this...
This study considers the prediction of driver's cognitive states from electroencephalographic (EEG) data. Extracting EEG features correlated with driver's cognitive states is key for achieving accurate prediction. However, high dimensionality and temporal-and-spatial correlations of EEG data make extraction of effective features difficult. This study explores the approaches based on deep belief networks...
Essential genes play vital roles in bacterial survival and they are potential antimicrobial targets and cornerstones of synthetic biology. Accurate recognition of bacterial essential genes by computational methods becomes necessary because of high economical and time consumption in wet experiments. In this paper, we evaluated the effectiveness of four machine learning methods that are Support Vector...
Recently, light-coding depth cameras, with their relatively good performance, have been widely used for depth image generation. To extend the field of view, multiple depth cameras usually have to be employed for scene representation and reconstruction. However, the interference among multiple light-coding depth cameras degrades the quality of depth images significantly. In this paper, we present an...
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