This paper addresses a modified auxiliary model stochastic gradient recursive parameter identification algorithm(M-AM-SGRPIA)for a class of single input single output(SISO)linear output error models with multi-thresho...This paper addresses a modified auxiliary model stochastic gradient recursive parameter identification algorithm(M-AM-SGRPIA)for a class of single input single output(SISO)linear output error models with multi-threshold quantized observations.It proves the convergence of the designed algorithm.A pattern-moving-based system dynamics description method with hybrid metrics is proposed for a kind of practical single input multiple output(SIMO)or SISO nonlinear systems,and a SISO linear output error model with multi-threshold quantized observations is adopted to approximate the unknown system.The system input design is accomplished using the measurement technology of random repeatability test,and the probabilistic characteristic of the explicit metric value is employed to estimate the implicit metric value of the pattern class variable.A modified auxiliary model stochastic gradient recursive algorithm(M-AM-SGRA)is designed to identify the model parameters,and the contraction mapping principle proves its convergence.Two numerical examples are given to demonstrate the feasibility and effectiveness of the achieved identification algorithm.展开更多
In order to improve the global search ability of biogeography-based optimization(BBO)algorithm in multi-threshold image segmentation,a multi-threshold image segmentation based on improved BBO algorithm is proposed.Whe...In order to improve the global search ability of biogeography-based optimization(BBO)algorithm in multi-threshold image segmentation,a multi-threshold image segmentation based on improved BBO algorithm is proposed.When using BBO algorithm to optimize threshold,firstly,the elitist selection operator is used to retain the optimal set of solutions.Secondly,a migration strategy based on fusion of good solution and pending solution is introduced to reduce premature convergence and invalid migration of traditional migration operations.Thirdly,to reduce the blindness of traditional mutation operations,a mutation operation through binary computation is created.Then,it is applied to the multi-threshold image segmentation of two-dimensional cross entropy.Finally,this method is used to segment the typical image and compared with two-dimensional multi-threshold segmentation based on particle swarm optimization algorithm and the two-dimensional multi-threshold image segmentation based on standard BBO algorithm.The experimental results show that the method has good convergence stability,it can effectively shorten the time of iteration,and the optimization performance is better than the standard BBO algorithm.展开更多
In order to obtain the image of airframe damage region and provide the input data for aircraft intelligent maintenance,a multi-dimensional and multi-threshold airframe damage region division method based on correlatio...In order to obtain the image of airframe damage region and provide the input data for aircraft intelligent maintenance,a multi-dimensional and multi-threshold airframe damage region division method based on correlation optimization is proposed.On the basis of airframe damage feature analysis,the multi-dimensional feature entropy is defined to realize the full fusion of multiple feature information of the image,and the division method is extended to multi-threshold to refine the damage division and reduce the impact of the damage adjacent region’s morphological changes on the division.Through the correlation parameter optimization algorithm,the problem of low efficiency of multi-dimensional multi-threshold division method is solved.Finally,the proposed method is compared and verified by instances of airframe damage image.The results show that compared with the traditional threshold division method,the damage region divided by the proposed method is complete and accurate,and the boundary is clear and coherent,which can effectively reduce the interference of many factors such as uneven luminance,chromaticity deviation,dirt attachment,image compression,and so on.The correlation optimization algorithm has high efficiency and stable convergence,and can meet the requirements of aircraft intelligent maintenance.展开更多
Hiding secret data in digital images is one of the major researchfields in information security.Recently,reversible data hiding in encrypted images has attracted extensive attention due to the emergence of cloud servi...Hiding secret data in digital images is one of the major researchfields in information security.Recently,reversible data hiding in encrypted images has attracted extensive attention due to the emergence of cloud services.This paper proposes a novel reversible data hiding method in encrypted images based on an optimal multi-threshold block labeling technique(OMTBL-RDHEI).In our scheme,the content owner encrypts the cover image with block permutation,pixel permutation,and stream cipher,which preserve the in-block correlation of pixel values.After uploading to the cloud service,the data hider applies the prediction error rearrangement(PER),the optimal threshold selection(OTS),and the multi-threshold labeling(MTL)methods to obtain a compressed version of the encrypted image and embed secret data into the vacated room.The receiver can extract the secret,restore the cover image,or do both according to his/her granted authority.The proposed MTL labels blocks of the encrypted image with a list of threshold values which is optimized with OTS based on the features of the current image.Experimental results show that labeling image blocks with the optimized threshold list can efficiently enlarge the amount of vacated room and thus improve the embedding capacity of an encrypted cover image.Security level of the proposed scheme is analyzed and the embedding capacity is compared with state-of-the-art schemes.Both are concluded with satisfactory performance.展开更多
Automatic edge detection of an image is considered a type of crucial information that can be extracted by applying detectors with different techniques. It is a main tool in pattern recognition, image segmentation, and...Automatic edge detection of an image is considered a type of crucial information that can be extracted by applying detectors with different techniques. It is a main tool in pattern recognition, image segmentation, and scene analysis. This paper introduces an edge-detection algorithm, which generates multi-threshold values. It is based on non-Shannon measures such as Havrda & Charvat’s entropy, which is commonly used in gray level image analysis in many types of images such as satellite grayscale images. The proposed edge detection performance is compared to the previous classic methods, such as Roberts, Prewitt, and Sobel methods. Numerical results underline the robustness of the presented approach and different applications are shown.展开更多
对于多用户中继系统中上行反馈量过大的问题,研究提出了一种基于多门限减少反馈的半分布式调度算法.该算法在基站与中继分别设置反馈门限,依据在多门限假设下可以得到总反馈用户数表达式,进而算出多个门限值;又根据中断概率算得一个门限...对于多用户中继系统中上行反馈量过大的问题,研究提出了一种基于多门限减少反馈的半分布式调度算法.该算法在基站与中继分别设置反馈门限,依据在多门限假设下可以得到总反馈用户数表达式,进而算出多个门限值;又根据中断概率算得一个门限,将该门限值作为多门限的下限.将两种门限值相结合以限制用户反馈量.对AF(Amplify and Forward)协议下采用该算法的反馈用户数及系统容量等性能指标给出了理论推导.仿真结果表明,该算法可较单门限算法进一步地减少反馈量,并降低系统的反馈中断概率,增大了系统容量.展开更多
基金This work was supported by the National Natural Science Foundation of China(62076025).
文摘This paper addresses a modified auxiliary model stochastic gradient recursive parameter identification algorithm(M-AM-SGRPIA)for a class of single input single output(SISO)linear output error models with multi-threshold quantized observations.It proves the convergence of the designed algorithm.A pattern-moving-based system dynamics description method with hybrid metrics is proposed for a kind of practical single input multiple output(SIMO)or SISO nonlinear systems,and a SISO linear output error model with multi-threshold quantized observations is adopted to approximate the unknown system.The system input design is accomplished using the measurement technology of random repeatability test,and the probabilistic characteristic of the explicit metric value is employed to estimate the implicit metric value of the pattern class variable.A modified auxiliary model stochastic gradient recursive algorithm(M-AM-SGRA)is designed to identify the model parameters,and the contraction mapping principle proves its convergence.Two numerical examples are given to demonstrate the feasibility and effectiveness of the achieved identification algorithm.
基金Science and Technology Plan of Gansu Province(No.144NKCA040)
文摘In order to improve the global search ability of biogeography-based optimization(BBO)algorithm in multi-threshold image segmentation,a multi-threshold image segmentation based on improved BBO algorithm is proposed.When using BBO algorithm to optimize threshold,firstly,the elitist selection operator is used to retain the optimal set of solutions.Secondly,a migration strategy based on fusion of good solution and pending solution is introduced to reduce premature convergence and invalid migration of traditional migration operations.Thirdly,to reduce the blindness of traditional mutation operations,a mutation operation through binary computation is created.Then,it is applied to the multi-threshold image segmentation of two-dimensional cross entropy.Finally,this method is used to segment the typical image and compared with two-dimensional multi-threshold segmentation based on particle swarm optimization algorithm and the two-dimensional multi-threshold image segmentation based on standard BBO algorithm.The experimental results show that the method has good convergence stability,it can effectively shorten the time of iteration,and the optimization performance is better than the standard BBO algorithm.
基金supported by the Aeronautical Science Foundation of China(No.20151067003)。
文摘In order to obtain the image of airframe damage region and provide the input data for aircraft intelligent maintenance,a multi-dimensional and multi-threshold airframe damage region division method based on correlation optimization is proposed.On the basis of airframe damage feature analysis,the multi-dimensional feature entropy is defined to realize the full fusion of multiple feature information of the image,and the division method is extended to multi-threshold to refine the damage division and reduce the impact of the damage adjacent region’s morphological changes on the division.Through the correlation parameter optimization algorithm,the problem of low efficiency of multi-dimensional multi-threshold division method is solved.Finally,the proposed method is compared and verified by instances of airframe damage image.The results show that compared with the traditional threshold division method,the damage region divided by the proposed method is complete and accurate,and the boundary is clear and coherent,which can effectively reduce the interference of many factors such as uneven luminance,chromaticity deviation,dirt attachment,image compression,and so on.The correlation optimization algorithm has high efficiency and stable convergence,and can meet the requirements of aircraft intelligent maintenance.
基金the Ministry of Science and Technology of Taiwan,Grant Number MOST 110-2221-E-507-003.
文摘Hiding secret data in digital images is one of the major researchfields in information security.Recently,reversible data hiding in encrypted images has attracted extensive attention due to the emergence of cloud services.This paper proposes a novel reversible data hiding method in encrypted images based on an optimal multi-threshold block labeling technique(OMTBL-RDHEI).In our scheme,the content owner encrypts the cover image with block permutation,pixel permutation,and stream cipher,which preserve the in-block correlation of pixel values.After uploading to the cloud service,the data hider applies the prediction error rearrangement(PER),the optimal threshold selection(OTS),and the multi-threshold labeling(MTL)methods to obtain a compressed version of the encrypted image and embed secret data into the vacated room.The receiver can extract the secret,restore the cover image,or do both according to his/her granted authority.The proposed MTL labels blocks of the encrypted image with a list of threshold values which is optimized with OTS based on the features of the current image.Experimental results show that labeling image blocks with the optimized threshold list can efficiently enlarge the amount of vacated room and thus improve the embedding capacity of an encrypted cover image.Security level of the proposed scheme is analyzed and the embedding capacity is compared with state-of-the-art schemes.Both are concluded with satisfactory performance.
文摘Automatic edge detection of an image is considered a type of crucial information that can be extracted by applying detectors with different techniques. It is a main tool in pattern recognition, image segmentation, and scene analysis. This paper introduces an edge-detection algorithm, which generates multi-threshold values. It is based on non-Shannon measures such as Havrda & Charvat’s entropy, which is commonly used in gray level image analysis in many types of images such as satellite grayscale images. The proposed edge detection performance is compared to the previous classic methods, such as Roberts, Prewitt, and Sobel methods. Numerical results underline the robustness of the presented approach and different applications are shown.
文摘对于多用户中继系统中上行反馈量过大的问题,研究提出了一种基于多门限减少反馈的半分布式调度算法.该算法在基站与中继分别设置反馈门限,依据在多门限假设下可以得到总反馈用户数表达式,进而算出多个门限值;又根据中断概率算得一个门限,将该门限值作为多门限的下限.将两种门限值相结合以限制用户反馈量.对AF(Amplify and Forward)协议下采用该算法的反馈用户数及系统容量等性能指标给出了理论推导.仿真结果表明,该算法可较单门限算法进一步地减少反馈量,并降低系统的反馈中断概率,增大了系统容量.
