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| 1 | On fast estimation of direction of arrival for underwater acoustic target based on sparse Bayesian learning显示文摘The Direction of Arrival(DOA) estimation methods for underwater acoustic target using Temporally Multiple Sparse Bayesian Learning(TMSBL) as the reconstructing algorithm have the disadvantage of slow computing speed.To solve this problem,a fast underwater acoustic target direction of arrival estimation was proposed.Analyzing the model characteristics of block-sparse Bayesian learning framework for DOA estimation,an algorithm was proposed to obtain the value of core hyper-parameter through MacKay's fixed-point method to estimate the DOA.By this process,it will spend less time for computation and provide more superior recovery performance than TMSBL algorithm.Simulation results verified the feasibiUty and effectiveness of the proposed algorithm. | WANG Biao ZHU Zhihui DAI Yuewei | 2017 | Chinese Journal of Acoustics2017，36，1： | 9 |
| 2 | Improved quantum bacterial foraging algorithm for tuning parameters of fractional-order PID controller显示文摘The quantum bacterial foraging optimization(QBFO)algorithm has the characteristics of strong robustness and global searching ability. In the classical QBFO algorithm, the rotation angle updated by the rotation gate is discrete and constant,which cannot affect the situation of the solution space and limit the diversity of bacterial population. In this paper, an improved QBFO(IQBFO) algorithm is proposed, which can adaptively make the quantum rotation angle continuously updated and enhance the global search ability. In the initialization process, the modified probability of the optimal rotation angle is introduced to avoid the existence of invariant solutions. The modified operator of probability amplitude is adopted to further increase the population diversity.The tests based on benchmark functions verify the effectiveness of the proposed algorithm. Moreover, compared with the integerorder PID controller, the fractional-order proportion integration differentiation(PID) controller increases the complexity of the system with better flexibility and robustness. Thus the fractional-order PID controller is applied to the servo system. The tuning results of PID parameters of the fractional-order servo system show that the proposed algorithm has a good performance in tuning the PID parameters of the fractional-order servo system. | LIU Lu SHAN Liang DAI Yuewei LIU Chenglin QI Zhidong | 2018 | Journal of Systems Engineering and Electronics2018，29，1： | 6 |
| 3 | PHOTOREALISTIC COMPUTER GRAPHICS FORENSICS BASED ON LEADING DIGIT LAW显示文摘As the advent and growing popularity of image rendering software,photorealistic computer graphics are becoming more and more perceptually indistinguishable from photographic images.If the faked images are abused,it may lead to potential social,legal or private consequences.To this end,it is very necessary and also challenging to find effective methods to differentiate between them.In this paper,a novel leading digit law,also called Benford's law,based method to identify computer graphics is proposed.More specifically,statistics of the most significant digits are extracted from image's Discrete Cosine Transform(DCT) coefficients and magnitudes of image's gradient,and then the Support Vector Machine(SVM) based classifiers are built.Results of experiments on the image datasets indicate that the proposed method is comparable to prior works.Besides,it possesses low dimensional features and low computational complexity. | Xu Bo Wang Junwen Liu Guangjie Dai Yuewei | 2011 | Journal of Electronics(China)2011，28，1： | 3 |
| 4 | A secret sharing based on (t, n) threshold and adversary structure显示文摘 | Qin Huawang Dai Yuewei Wang Zhiquan | 2009 | Int J Secur2009，，8： | 1 |
| 5 | Locally Optimum Detection for Barni's Multiplicative Watermarking in DWT Domain显示文摘 | Wang Jinwei Liu Guangjie Dai Yuewei | | 0，，01： | 1 |
| 6 | A Model of Intrusion Tolerant System Based on Game Theory显示文摘 | Huawang Qin Yuewei Dai Zhiquan Wang | 2009 | Computer and Information Science2009，，11： | 1 |
| 7 | Locally opti- mum detection for Barni' s mtdtiplicative watermarking in DWT domain显示文摘 | Wang Jinwei Liu Guangjie Dai Yuewei | 2008 | Signal Processing2008，88，1： | 1 |
| 8 | Syndrome trellis codes based on minimal span generator matrix 显示文摘 | Liu Weiwei Liu Guangjie Dai Yuewei | 2014 | Annals of Telecommunications-Annales des Tlcommunications2014，69，78： | 1 |
| 9 | Damage-re- sistance matrix embedding framework: the contradic- tion between robustness and embedding efficiency 显示文摘 | Liu Weiwei Liu Guangjie Dai Yuewei | 2015 | Security and Communication Networks2015，8，： | 1 |
| 10 | Detecting JPEG image forgery based on double compression显示文摘Detecting the forgery parts from a double compressed image is very important and urgent work for blind authentication.A very simple and efficient method for accomplishing the task is proposed.Firstly,the probabilistic model with periodic effects in double quantization is analyzed,and the probability of quantized DCT coefficients in each block is calculated over the entire image.Secondly,the posteriori probability of each block is computed according to Bayesian theory and the results mentioned in first part.Then the mean and variance of the posteriori probability are to be used for judging whether the target block is tampered.Finally,the mathematical morphology operations are performed to reduce the false alarm probability.Experimental results show that the method can exactly locate the doctored part,and through the experiment it is also found that for detecting the tampered regions,the higher the second compression quality is the more exact the detection efficiency is. | Wang Junwen Liu Guangjie Dai Yuewei Wang Zhiquan | 2009 | Journal of Systems Engineering and Electronics2009，20，5： | 1 |
| 11 | Boosting Adversarial Training with Learnable Distribution显示文摘In recent years,various adversarial defense methods have been proposed to improve the robustness of deep neural networks.Adversarial training is one of the most potent methods to defend against adversarial attacks.However,the difference in the feature space between natural and adversarial examples hinders the accuracy and robustness of the model in adversarial training.This paper proposes a learnable distribution adversarial training method,aiming to construct the same distribution for training data utilizing the Gaussian mixture model.The distribution centroid is built to classify samples and constrain the distribution of the sample features.The natural and adversarial examples are pushed to the same distribution centroid to improve the accuracy and robustness of the model.The proposed method generates adversarial examples to close the distribution gap between the natural and adversarial examples through an attack algorithm explicitly designed for adversarial training.This algorithm gradually increases the accuracy and robustness of the model by scaling perturbation.Finally,the proposed method outputs the predicted labels and the distance between the sample and the distribution centroid.The distribution characteristics of the samples can be utilized to detect adversarial cases that can potentially evade the model defense.The effectiveness of the proposed method is demonstrated through comprehensive experiments. | Kai Chen Jinwei Wang James Msughter Adeke Guangjie Liu Yuewei Dai | 2024 | Computers, Materials & Continua2024，78，3： | 0 |
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