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Multi-focus image fusion based on fractional-order derivative and intuitionistic fuzzy sets Research Articles

Xue-feng Zhang, Hui Yan, Hao He,zhangxuefeng@mail.neu.edu.cn

Frontiers of Information Technology & Electronic Engineering 2020, Volume 21, Issue 6,   Pages 809-962 doi: 10.1631/FITEE.1900737

Abstract: Multi-focus is an increasingly important component in , and it plays a key role in imaging. In this paper, we put forward a novel multi-focus method which employs and . The original image is decomposed into a base layer and a detail layer. Furthermore, a new fractional-order spatial frequency is built to reflect the clarity of the image. The fractional-order spatial frequency is used as a rule for detail layers fusion, and are introduced to fuse base layers. Experimental results demonstrate that the proposed fusion method outperforms the state-of-the-art methods for multi-focus .

Keywords： 像融合；分数阶导数；直觉模糊集；多聚焦图像    

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An improved ROF denoising model based on time-fractional derivative Research Articles

Xing-ran Liao,xrliao_scu@163.com

Frontiers of Information Technology & Electronic Engineering 2020, Volume 21, Issue 6,   Pages 809-962 doi: 10.1631/FITEE.2000067

Abstract: In this study, we discuss mainly the and texture retention issues. Usually, the has an adjustable fractional order to control the diffusion process, and its memory effect can nicely retain the image texture when it is applied to . Therefore, we design a new Rudin-Osher-Fatemi model with a based on a classical one, where the discretization in space is based on the integer-order difference scheme and the discretization in time is the approximation of the (i.e., Caputo-like difference is applied to discretize the ). Stability and convergence of such an explicit scheme are analyzed in detail. We prove that the numerical solution to the new model converges to the exact solution with the order of (+), where , , and are the time step size, fractional order, and space step size, respectively. Finally, various evaluation criteria including the signal-to-noise ratio, feature similarity, and histogram recovery degree are used to evaluate the performance of our new model. Numerical test results show that our improved model has more powerful denoising and texture retention ability than existing ones.

Keywords： 改进ROF去噪模型；时间分数阶导数；Caputo导数；图像去噪    

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Fractional-order global optimal backpropagation machine trained by an improved fractional-order steepest descent method Research Articles

Yi-fei Pu, Jian Wang,puyifei@scu.edu.cn,wangjiannl@upc.edu.cn

Frontiers of Information Technology & Electronic Engineering 2020, Volume 21, Issue 6,   Pages 809-962 doi: 10.1631/FITEE.1900593

Abstract: We introduce the fractional-order global optimal backpropagation machine, which is trained by an improved (FSDM). This is a fractional-order backpropagation neural network (FBPNN), a state-of-the-art fractional-order branch of the family of backpropagation neural networks (BPNNs), different from the majority of the previous classic first-order BPNNs which are trained by the traditional first-order steepest descent method. The reverse incremental search of the proposed FBPNN is in the negative directions of the approximate fractional-order partial derivatives of the square error. First, the theoretical concept of an FBPNN trained by an improved FSDM is described mathematically. Then, the mathematical proof of fractional-order global optimal convergence, an assumption of the structure, and of the FBPNN are analyzed in detail. Finally, we perform three (types of) experiments to compare the performances of an FBPNN and a classic first-order BPNN, i.e., example function approximation, , and comparison of global search and error fitting abilities with real data. The higher optimal search ability of an FBPNN to determine the global optimal solution is the major advantage that makes the FBPNN superior to a classic first-order BPNN.

Keywords： 分数阶微积分；分数阶反向传播算法；分数阶最速下降法；均方误差；分数阶多尺度全局优化    

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A Method of Information Fusion Based on Rough Sets and Its Applications

Chen Shuangye,Zhang Weijing

Strategic Study of CAE 2006, Volume 8, Issue 12,   Pages 75-79

Abstract:

A method of multi-sensor information fusion based on rough sets and fuzzy logic is proposed in this paper. Rough-fuzzy model can be built by obtaining general simplified rules from the large number of data using rough sets theory and methods of computing reduces. The concepts of expansion and perfection to the model are also presented. Finally the simulations and experiments of pulse vacuum disinfection control system are carried out using this method, the research results show the method is effective and feasible.

Keywords： information fusion     rough sets     fuzzy logic     rough-fuzzy model    

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Discrete fractional watermark technique Correspondence

Zai-rong Wang, Babak Shiri, Dumitru Baleanu,wangzr@njtc.edu.cn,shire_babak@yahoo.com,dumitru@cankaya.edu.tr

Frontiers of Information Technology & Electronic Engineering 2020, Volume 21, Issue 6,   Pages 809-962 doi: 10.1631/FITEE.2000133

Abstract: The fractional logistic map holds rich dynamics and is adopted to generate chaotic series. A image is then encrypted and inserted into the original images. Since the encryption image takes the fractional order within (0, 1], it increases the key space and becomes difficult to attack. This study provides a robust method in the protection of the copyright of hardware, images, and other electronic files.

Keywords： 离散分数阶微积分；图像加密；水印    

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A New Two_dimensional Linear Discriminant Analysis Algori thmBased on Fuzzy Set Theory

Zheng Yujie,Yang Jingyu,Wu Xiaojun, Li Yongzhi

Strategic Study of CAE 2007, Volume 9, Issue 2,   Pages 49-53

Abstract:

2DLDA algorithm is based on2D matrices and overleaps the step of transforming the matrices into the corresponding vectors,which is done on conventional LDA algorithm.However,performance of recognition rate may always be degraded by the overlapping(outlier)samples et al in the field of pattern recognition.How to avoid these shortcomings and extract optimal features to improve the performance of recognition is a key step. In this paper,a new2DLDA algorithm,named fuzzy2DLDA,is proposed.Fuzzy k-nearest neighbour(FKNN) is implemented first to achieve the distribution information of original samples represented with fuzzy membership degrees and is incorporated into the process of feature extraction.The proposed algorithm inherits the virtue of conventional2DLDA and suppresses the shortcoming resulted by overlappin g(outlier)samples et al. Experimental results on AT&T face database demonstrate rec ognition rates of the proposed algorithm outperform that of conventional2DLDA and fisherface.

Keywords： two-dimensional linear discriminant analysis(2DLDA)     fuzzy two-dimensional linear    

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A decision-making method about the design quality of component-based active load section entity model for protective engineering

Yuan Hui,Wang Fengshan,Xu Jiheng,Fu Chengqun

Strategic Study of CAE 2013, Volume 15, Issue 5,   Pages 106-112

Abstract:

To effectively express the protective engineering space object, and effectively support various topology operation and military damage applications, a component-based entity model design scheme and its quality was proposed for the active load section of protective engineering. According to the design variety and validity confirmation in component-based protective engineering entity model, the positive and negative ideal intuitionistic fuzzy design project was determined, and respectively comparing the distance from the design project to the positive and negative ideal project, the superiority degree model was established for the component-based entity model design projects, which further gained the sequence of such projects. Case showed that model effectively solved the decision-making problem about entity model design operations, which provided one theory and method for scientific decision-making practice in entity model design operation for such active load section of protective engineering.

Keywords： protective engineering     component     design quality     entity model     intuitionistic fuzzy sets     superiority    

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Rule-base Self-extraction and Simplification for Fuzzy Systems

Guo Haixiang,Liu Tao,Zhu Kejun

Strategic Study of CAE 2004, Volume 6, Issue 10,   Pages 52-58

Abstract:

In this paper, a fuzzy model algorithm for a rule-base self-extraction and simplification is introduced. The method consistes of three steps: The first step is to classify the out-in space by constructing a fuzzy partition validity index, then the optimal number of dusters and, hence, the optimal number of rules are obtained; The second step is to construct the initial fuzzy system based on the optimal number of rules and neural networks; The third step is to get the function of computing similarity of fuzzy sets by fuzzy similarity analysis method. The similar fuzzy sets are merged to create a common fuzzy set in rule base based on threshold value. Thus a fuzzy system with interpretability and simplicity is obtained. At last, the fuzzy rules of productivity factor of China is extracted by the fuzzy system.

Keywords： similarity measures     fuzzy model     fuzzy rules     fuzzy sets    

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A novel color image encryption algorithm based on a fractional-order discrete chaotic neural network and DNA sequence operations Research Articles

Li-ping Chen, Hao Yin, Li-guo Yuan, António M. Lopes, J. A. Tenreiro Machado, Ran-chao Wu,lip_chenhut@126.com

Frontiers of Information Technology & Electronic Engineering 2020, Volume 21, Issue 6,   Pages 809-962 doi: 10.1631/FITEE.1900709

Abstract: A novel algorithm based on dynamic deoxyribonucleic acid (DNA) encoding and chaos is presented. A three-neuron fractional-order discrete Hopfield neural network (FODHNN) is employed as a pseudo-random chaotic sequence generator. Its initial value is obtained with the secret key generated by a five-parameter external key and a hash code of the plain image. The external key includes both the FODHNN discrete step size and order. The hash is computed with the SHA-2 function. This ensures a large secret key space and improves the algorithm sensitivity to the plain image. Furthermore, a new three-dimensional projection confusion method is proposed to scramble the pixels among red, green, and blue color components. DNA encoding and diffusion are used to diffuse the image information. Pseudo-random sequences generated by FODHNN are employed to determine the encoding rules for each pixel and to ensure the diversity of the encoding methods. Finally, confusion II and XOR are used to ensure the security of the encryption. Experimental results and the security analysis show that the proposed algorithm has better performance than those reported in the literature and can resist typical attacks.

Keywords： 分数阶离散系统；神经网络；DNA加密；彩色图像加密    

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Fractional-order memristive neural synaptic weighting achieved by pulse-based fracmemristor bridge circuit Research Articles

Yifei Pu, Bo Yu, Qiuyan He, Xiao Yuan,heqiuyan789@163.com,yuanxiao@scu.edu.cn

Frontiers of Information Technology & Electronic Engineering 2021, Volume 22, Issue 6,   Pages 862-876 doi: 10.1631/FITEE.2000085

Abstract: We propose a novel circuit for the fractional-order memristive neural synaptic weighting (FMNSW). The introduced circuit is different from the majority of the previous integer-order approaches and offers important advantages. Since the concept of memristor has been generalized from the classic integer-order memristor to the (), a challenging theoretical problem would be whether the can be employed to implement the or not. In this research, characteristics of the FMNSW, realized by a pulse-based bridge circuit, are investigated. First, the circuit configuration of the FMNSW is explained using a pulse-based bridge circuit. Second, the mathematical proof of the fractional-order learning capability of the FMNSW is analyzed. Finally, experimental work and analyses of the electrical characteristics of the FMNSW are presented. Strong ability of the FMNSW in explaining the cellular mechanisms that underlie learning and memory, which is superior to the traditional integer-order memristive neural synaptic weighting, is considered a major advantage for the proposed circuit.

Keywords： 分数阶微积分；分忆抗；分忆抗值；分数阶忆阻；分数阶记忆性突触    

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Bifurcation-based fractional-order PI None

Karima RABAH, Samir LADACI, Mohamed LASHAB

Frontiers of Information Technology & Electronic Engineering 2018, Volume 19, Issue 2,   Pages 180-191 doi: 10.1631/FITEE.1601543

Abstract: We propose a novel approach called the robust fractional-order proportional-integral-derivative (FOPID) controller, to stabilize a perturbed nonlinear chaotic system on one of its unstable fixed points. The stability analysis of the nonlinear chaotic system is made based on the proportional-integral-derivative actions using the bifurcation diagram. We extract an initial set of controller parameters, which are subsequently optimized using a quadratic criterion. The integral and derivative fractional orders are also identified by this quadratic criterion. By applying numerical simulations on two nonlinear systems, namely the multi-scroll Chen system and the Genesio-Tesi system, we show that the fractional PIλDμ controller provides the best closed-loop system performance in stabilizing the unstable fixed points, even in the presence of random perturbation.

Keywords： Fractional order system     Bifurcation diagram     Fractional PIλDμ controller     Multi-scroll Chen chaotic system     Genesio-Tesi chaotic system    

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Multi-focus image fusion based on fully convolutional networks Research Articles

Rui Guo, Xuan-jing Shen, Xiao-yu Dong, Xiao-li Zhang,zhangxiaoli@jlu.edu.cn

Frontiers of Information Technology & Electronic Engineering 2020, Volume 21, Issue 7,   Pages 963-1118 doi: 10.1631/FITEE.1900336

Abstract: We propose a method, in which a fully convolutional network for focus detection (FD-FCN) is constructed. To obtain more precise focus detection maps, we propose to add s in the network to make both detailed and abstract visual information available when using FD-FCN to generate maps. A new training dataset for the proposed network is constructed based on dataset CIFAR-10. The image fusion algorithm using FD-FCN contains three steps: focus maps are obtained using FD-FCN, decision map generation occurs by applying a morphological process on the focus maps, and image fusion occurs using a decision map. We carry out several sets of experiments, and both subjective and objective assessments demonstrate the superiority of the proposed fusion method to state-of-the-art algorithms.

Keywords： 多焦距图像融合；全卷积网络；跳层；性能评估    

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Design of a fractional PI None

Pritesh SHAH, Sudhir AGASHE, Anand J. KULKARNI

Frontiers of Information Technology & Electronic Engineering 2018, Volume 19, Issue 3,   Pages 437-445 doi: 10.1631/FITEE.1601495

Abstract: The cohort intelligence (CI) method has recently evolved as an optimization method based on artificial intelligence. We use the CI method for the first time to optimize the parameters of the fractional proportionalintegral-derivative (PID) controller. The performance of the CI method in designing the fractional PID controller was validated and compared with those of some other popular algorithms such as particle swarm optimization, the genetic algorithm, and the improved electromagnetic algorithm. The CI method yielded improved solutions in terms of the cost function, computing time, and function evaluations in comparison with the other three algorithms. In addition, the standard deviations of the CI method demonstrated the robustness of the proposed algorithm in solving control problems.

Keywords： Cohort intelligence     Fractional calculus     Fractional PID controller     Tuning    

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Recent advances in multisensor multitarget tracking using random finite set Review Articles

Kai Da, Tiancheng Li, Yongfeng Zhu, Hongqi Fan, Qiang Fu,dktm131@163.com,t.c.li@nwpu.edu.cn,zoyofo@163.com,fanhongqi@nudt.edu.cn

Frontiers of Information Technology & Electronic Engineering 2021, Volume 22, Issue 1,   Pages 1-140 doi: 10.1631/FITEE.2000266

Abstract: In this study, we provide an overview of recent advances in multisensor based on the (RFS) approach. The fusion that plays a fundamental role in multisensor filtering is classified into data-level multitarget measurement fusion and estimate-level multitarget density fusion, which share and fuse local measurements and posterior densities between sensors, respectively. Important properties of each fusion rule including the optimality and sub-optimality are presented. In particular, two robust multitarget density-averaging approaches, arithmetic- and geometric-, are addressed in detail for various RFSs. Relevant research topics and remaining challenges are highlighted.

Keywords： Multitarget tracking     Multisensor fusion     Average fusion     Random finite set     Optimal fusion    

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A fractional-order multifunctionaln-step honeycomb RLC circuit network Article

Ling ZHOU, Zhi-zhong TAN, Qing-hua ZHANG

Frontiers of Information Technology & Electronic Engineering 2017, Volume 18, Issue 8,   Pages 1186-1196 doi: 10.1631/FITEE.1601560

Abstract: We investigate a multifunctional -step honeycomb network which has not been studied before. By adjusting the circuit parameters, such a network can be transformed into several different networks with a variety of functions, such as a regular ladder network and a triangular network. We derive two new formulae for equivalent resistance in the resistor network and equivalent impedance in the LC network, which are in the fractional-order domain. First, we simplify the complex network into a simple equivalent model. Second, using Kirchhoff’s laws, we establish a fractional difference equation. Third, we construct an equivalent transformation method to obtain a general solution for the nonlinear differential equation. In practical applications, several interesting special results are obtained. In particular, an step impedance LC network is discussed and many new characteristics of complex impedance have been found.

Keywords： Honeycomb network     Equivalent transformation     Fractional differential equation     Impedance characteristics    

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Title Author Date Type Operation

Multi-focus image fusion based on fractional-order derivative and intuitionistic fuzzy sets

Xue-feng Zhang, Hui Yan, Hao He,zhangxuefeng@mail.neu.edu.cn

Journal Article

An improved ROF denoising model based on time-fractional derivative

Xing-ran Liao,xrliao_scu@163.com

Journal Article

Fractional-order global optimal backpropagation machine trained by an improved fractional-order steepest descent method

Yi-fei Pu, Jian Wang,puyifei@scu.edu.cn,wangjiannl@upc.edu.cn

Journal Article

A Method of Information Fusion Based on Rough Sets and Its Applications

Chen Shuangye,Zhang Weijing

Journal Article

Discrete fractional watermark technique

Zai-rong Wang, Babak Shiri, Dumitru Baleanu,wangzr@njtc.edu.cn,shire_babak@yahoo.com,dumitru@cankaya.edu.tr

Journal Article

A New Two_dimensional Linear Discriminant Analysis Algori thmBased on Fuzzy Set Theory

Zheng Yujie,Yang Jingyu,Wu Xiaojun, Li Yongzhi

Journal Article

A decision-making method about the design quality of component-based active load section entity model for protective engineering

Yuan Hui,Wang Fengshan,Xu Jiheng,Fu Chengqun

Journal Article

Rule-base Self-extraction and Simplification for Fuzzy Systems

Guo Haixiang,Liu Tao,Zhu Kejun

Journal Article

A novel color image encryption algorithm based on a fractional-order discrete chaotic neural network and DNA sequence operations

Li-ping Chen, Hao Yin, Li-guo Yuan, António M. Lopes, J. A. Tenreiro Machado, Ran-chao Wu,lip_chenhut@126.com

Journal Article

Fractional-order memristive neural synaptic weighting achieved by pulse-based fracmemristor bridge circuit

Yifei Pu, Bo Yu, Qiuyan He, Xiao Yuan,heqiuyan789@163.com,yuanxiao@scu.edu.cn

Journal Article

Bifurcation-based fractional-order PI

Karima RABAH, Samir LADACI, Mohamed LASHAB

Journal Article

Multi-focus image fusion based on fully convolutional networks

Rui Guo, Xuan-jing Shen, Xiao-yu Dong, Xiao-li Zhang,zhangxiaoli@jlu.edu.cn

Journal Article

Design of a fractional PI

Pritesh SHAH, Sudhir AGASHE, Anand J. KULKARNI

Journal Article

Recent advances in multisensor multitarget tracking using random finite set

Kai Da, Tiancheng Li, Yongfeng Zhu, Hongqi Fan, Qiang Fu,dktm131@163.com,t.c.li@nwpu.edu.cn,zoyofo@163.com,fanhongqi@nudt.edu.cn

Journal Article

A fractional-order multifunctionaln-step honeycomb RLC circuit network

Ling ZHOU, Zhi-zhong TAN, Qing-hua ZHANG

Journal Article