A parametric Colored Petri net model of the switched Ethernet network with the tree-like topology is developed. The model’s structure is the same for any given network and contains fixed number of nodes. The tree-lik...A parametric Colored Petri net model of the switched Ethernet network with the tree-like topology is developed. The model’s structure is the same for any given network and contains fixed number of nodes. The tree-like topology of a definite network is given as the marking of dedicated places. The model represents a network containing workstations, servers, switches, and provides the evaluation of the network response time. Besides topology, the parameters of the model are performances of hardware and software used within the network. Performance evaluation for the network of the railway dispatcher center is implemented. Topics of the steady-stable condition and the optimal choice of hardware are discussed.展开更多
Due to the mutual interference and sharing of wireless links in TDMA wireless sensor networks, conflicts will occur when data messages are transmitting between nodes. The broadcast scheduling problem （BSP） is aimed ...Due to the mutual interference and sharing of wireless links in TDMA wireless sensor networks, conflicts will occur when data messages are transmitting between nodes. The broadcast scheduling problem （BSP） is aimed to schedule each node in different slot of fixed length frame at least once, and the objective of BSP is to seek for the optimal feasible solution, which has the shortest length of frame slots, as well as the maximum node transmission. A two-stage mixed algorithm based on a fuzzy Hopfield neural network is proposed to solve this BSP in wireless sensor network. In the first stage, a modified sequential vertex coloring algorithm is adopted to obtain a minimal TDMA frame length. In the second stage, the fuzzy Hopfleld network is utilized to maximize the channel utilization ratio. Experimental results, obtained from the running on three benchmark graphs, show that the algorithm can achieve better performance with shorter frame length and higher channel utilizing ratio than other exiting BSP solutions.展开更多
The interactions of a colored dynamical network play a great role in its dynamical behaviour and are denoted by outer and inner coupling matrices. In this paper, the outer and inner coupting matrices are assumed to be...The interactions of a colored dynamical network play a great role in its dynamical behaviour and are denoted by outer and inner coupling matrices. In this paper, the outer and inner coupting matrices are assumed to be unknown and need to be identified. A corresponding network estimator is designed for identifying the unknown interactions by adopting proper adaptive laws. Based on the Lyapunov function method and Barbalat＇s lemma, the obtained result is analytically proved. A colored network coupled with chaotic Lorenz, Chen, and Lii systems is considered as a numerical example to illustrate the effectiveness of the proposed method.展开更多
This paper proposes a hybrid technique for color image segmentation. First an input image is converted to the image of CIE L＊a＊b＊ color space. The color features ＂a＂ and ＂b＂ of CIE L^＊a^＊b^＊ are then fed int...This paper proposes a hybrid technique for color image segmentation. First an input image is converted to the image of CIE L＊a＊b＊ color space. The color features ＂a＂ and ＂b＂ of CIE L^＊a^＊b^＊ are then fed into fuzzy C-means （FCM） clustering which is an unsupervised method. The labels obtained from the clustering method FCM are used as a target of the supervised feed forward neural network. The network is trained by the Levenberg-Marquardt back-propagation algorithm, and evaluates its performance using mean square error and regression analysis. The main issues of clustering methods are determining the number of clusters and cluster validity measures. This paper presents a method namely co-occurrence matrix based algorithm for finding the number of clusters and silhouette index values that are used for cluster validation. The proposed method is tested on various color images obtained from the Berkeley database. The segmentation results from the proposed method are validated and the classification accuracy is evaluated by the parameters sensitivity, specificity, and accuracy.展开更多
Fashion color forecasting is one of the most important factors for fashion marketing and manufacturing. Several models have been applied by previous researchers to conduct fashion color forecasting. However, few convi...Fashion color forecasting is one of the most important factors for fashion marketing and manufacturing. Several models have been applied by previous researchers to conduct fashion color forecasting. However, few convincing forecasting systems have been established. A prediction model for fashion color forecasting was established by applying an improved back propagation neural network (BPNN) model in this paper. Successive six-year fashion color palettes, released by INTERCOLOR, were used as learning information for the neural network to develop a reliable prediction model. Colors in the palettes were quantified by PANTONE color system. Additionally, performance of the established model was compared with other GM(1, 1) models. Results show that the improved BPNN model is suitable to predict future fashion color trend.展开更多
The colorant formulation using artificial neural networks (ANN) was investigated in this study. A simple 3 -layer, input - hidden - output system was constructed for the recipe formulation of one - , two - , and three...The colorant formulation using artificial neural networks (ANN) was investigated in this study. A simple 3 -layer, input - hidden - output system was constructed for the recipe formulation of one - , two - , and three -dye mixtures. Comprehensive tests were carried out to explore the properties of a 3 - layer simple ANN systematically . These properties include number of neurons in the hidden layer, learning rate of the network, momentum factor of the network, as well as the number of epochs for the learning process. The tests show accurate results for one - and two - dye mixtures while less accurate but comparable results to conventional colorant formulation systems for three - dye mixtures. It is also found that the optimum values of the neural network parameters are important towards the accuracy of the colorant formulation.展开更多
An evolutionary network driven by dynamics is studied and applied to the graph coloring problem. From an initial structure, both the topology and the coupling weights evolve according to the dynamics. On the other han...An evolutionary network driven by dynamics is studied and applied to the graph coloring problem. From an initial structure, both the topology and the coupling weights evolve according to the dynamics. On the other hand, the dynamics of the network are determined by the topology and the coupling weights, so an interesting structure-dynamics co-evolutionary scheme appears. By providing two evolutionary strategies, a network described by the complement of a graph will evolve into several clusters of nodes according to their dynamics. The nodes in each cluster can be assigned the same color and nodes in different clusters assigned different colors. In this way, a co-evolution phenomenon is applied to the graph coloring problem. The proposed scheme is tested on several benchmark graphs for graph coloring.展开更多
A method of the forward operation of color appearance (from colorimetric attributes to color appearance attributes) using an artificial neural network (ANN) is presented The neural network model developed is a multila...A method of the forward operation of color appearance (from colorimetric attributes to color appearance attributes) using an artificial neural network (ANN) is presented The neural network model developed is a multilayer feedforward neural network model for predicting color appearance model (CAM). This method greatly decreased the mathematical computation in color appearance prediction. The error backed-propagation (BP) algorithm was applied in the training of the neural networks, and it was trained and tested by the LUTCHI color appearance datasets which are the most comprehensive one in testing color appearance model. CRT was selected as a typical example in experiment because it is usually used as self-luminous object in fact, and several ways for choosing training samples were included and compared each other. The testing results show that the color appearance prediction using artificial neural network is well consistent with visual evaluation.展开更多
A CRT characterization method based on color appearance matching is presented. A matching between Munsell color chips and CRT charts was obtained in vision perceiver in typical office environment and viewing condition...A CRT characterization method based on color appearance matching is presented. A matching between Munsell color chips and CRT charts was obtained in vision perceiver in typical office environment and viewing condition by recommending. And neural networks were utilized to accomplish the color space conversion from CIE standard color space to CRT device color space. The neural networks related the color space conversion and color reproduction of soft/hard-copy directly to the influence of the illuminance and viewing condition in vision perceiver. The average color difference of training samples is 3.06 and that of testing samples is 5.17. The experiment results indicated that the neural networks can satisfy the requirements for the color appearance of hard-copy reproduction in CRT.展开更多
Systems using numerous cameras are emerging in many fields due to their ease of production and reduced cost, and one of the fields where they are expected to be used more actively in the near future is in image-based ...Systems using numerous cameras are emerging in many fields due to their ease of production and reduced cost, and one of the fields where they are expected to be used more actively in the near future is in image-based rendering （IBR）. Color correction between views is necessary to use multi-view systems in IBR to make audiences feel comfortable when views are switched or when a free viewpoint video is displayed. Color correction usually involves two steps： the first is to adjust camera parameters such as gain, brightness, and aperture before capture, and the second is to modify captured videos through image processing. This paper deals with the latter, which does not need a color pattern board. The proposed method uses scale invariant feature transform （SIFT） to detect correspondences, treats RGB channels independently, calculates lookup tables with an energy-minimization approach, and corrects captured video with these tables. The experimental results reveal that this approach works well.展开更多
The new topological indices A x1 A x3 suggested in our laboratories were applied to the study of structure property relationships between color reagents and their color reactions with yttrium. The ...The new topological indices A x1 A x3 suggested in our laboratories were applied to the study of structure property relationships between color reagents and their color reactions with yttrium. The topological indices of twenty asymmetrical phosphone bisazo derivatives of chromotropic acid were calculated. The work shows that QSPR can be used as a novel aid to predict the molar absorptivities of color reactions and in the long term to be helpful tool in color reagent design. Multiple regression analysis and neural network were employed simultaneously in this study. The results demonstrated the feasibility and the effectiveness of the method.展开更多
Improving routing algorithm performance not only leads to appreciate the quality of data transmission, but also increases the speed of data transfer. In this paper we propose a hybrid method which is a combination of ...Improving routing algorithm performance not only leads to appreciate the quality of data transmission, but also increases the speed of data transfer. In this paper we propose a hybrid method which is a combination of traffic classification by the help of colored pheromones and helping ants method in the intermediate nodes. This combination increases the convergence speed and decreases the delay and Jitter in the network. Also we compare the obtained results with two known routing algorithms that are based on the ant colony.展开更多
IEEE 802.11 based wireless mesh networks with directional antennas are expected to be a new promising technology and an economic approach for providing wireless broadband services in rural areas.In this paper,we discu...IEEE 802.11 based wireless mesh networks with directional antennas are expected to be a new promising technology and an economic approach for providing wireless broadband services in rural areas.In this paper,we discuss interference models and address how they can affect the design of channel assignment in rural mesh networks.We present a new channel assignment framework based on graph coloring for rural wireless mesh networks.The goal of the framework is to allow synchronously transmitting or receiving data from multiple neighbor links at the same time,and continuously doing full-duplex data transfer on every link,creating an efficient rural mesh network without interference.Channel assignment is shown to be NP-hard.We frame this channel allocation problem in terms of Adjacent Vertex Distinguishing Edge Coloring(AVDEC).Detailed assignment results on grid topology are presented and discussed.Furthermore,we design an algorithm.Finally,we evaluate the performance of the proposed algorithm through extensive simulations and show the algorithm is effective to the regular grid topologies,and the number of colors used by the algorithm is upper bounded by+1.Hence the algorithm guarantees that the number of channels available in standards such as IEEE802.11a is sufficient to have a valid AVDEC for many grid topologies.We also evaluate the proposed algorithm for arbitrary graphs.The algorithm provides a lower upper bound on the minimum number of channels to the AVDEC index channel assignment problem.展开更多
图像去模糊需要在保留空间细节的同时确保高层次的上下文信息的平衡.针对模糊图像中的空间结构破坏,上下文信息扭曲以及RGB图像中的通道间强相关性造成的颜色不平衡等问题,本文提出一种基于YUV颜色空间和图卷积网络(GCN)的图像去模糊算...图像去模糊需要在保留空间细节的同时确保高层次的上下文信息的平衡.针对模糊图像中的空间结构破坏,上下文信息扭曲以及RGB图像中的通道间强相关性造成的颜色不平衡等问题,本文提出一种基于YUV颜色空间和图卷积网络(GCN)的图像去模糊算法(YUVGCR).首先,设计了用于图像去模糊的YUV与RGB颜色空间转换算法,以解决RGB通道间强相关性的问题.然后,利用GCN可以将特征图转换为预生成图的顶点,对特征图进行图卷积,从而合成构建图结构的数据.通过这样做,可以隐式地将图拉普拉斯正则化应用于特征图,使其更加结构化.实验表明,YUVGCR的峰值信噪比(PSNR)为36.21 dB,比先进算法提高了2.93 d B.可视化去模糊结果可以看出,YUVGCR能产生更清晰的边缘和细节,图像去模糊的整体性能获得较大提升.展开更多
文摘A parametric Colored Petri net model of the switched Ethernet network with the tree-like topology is developed. The model’s structure is the same for any given network and contains fixed number of nodes. The tree-like topology of a definite network is given as the marking of dedicated places. The model represents a network containing workstations, servers, switches, and provides the evaluation of the network response time. Besides topology, the parameters of the model are performances of hardware and software used within the network. Performance evaluation for the network of the railway dispatcher center is implemented. Topics of the steady-stable condition and the optimal choice of hardware are discussed.
基金supported by the National Natural Science Foundation of China (60775047)Hunan Provincial Natural Science Foundation of China (07JJ6111)
文摘Due to the mutual interference and sharing of wireless links in TDMA wireless sensor networks, conflicts will occur when data messages are transmitting between nodes. The broadcast scheduling problem （BSP） is aimed to schedule each node in different slot of fixed length frame at least once, and the objective of BSP is to seek for the optimal feasible solution, which has the shortest length of frame slots, as well as the maximum node transmission. A two-stage mixed algorithm based on a fuzzy Hopfield neural network is proposed to solve this BSP in wireless sensor network. In the first stage, a modified sequential vertex coloring algorithm is adopted to obtain a minimal TDMA frame length. In the second stage, the fuzzy Hopfleld network is utilized to maximize the channel utilization ratio. Experimental results, obtained from the running on three benchmark graphs, show that the algorithm can achieve better performance with shorter frame length and higher channel utilizing ratio than other exiting BSP solutions.
基金supported by the National Natural Science Foundation of China(Grant No.61463022)the Natural Science Foundation of Jiangxi Educational Committee,China(Grant No.GJJ14273)the Graduate Innovation Fund of Jiangxi Normal University,China(Grant No.YJS2014061)
文摘The interactions of a colored dynamical network play a great role in its dynamical behaviour and are denoted by outer and inner coupling matrices. In this paper, the outer and inner coupting matrices are assumed to be unknown and need to be identified. A corresponding network estimator is designed for identifying the unknown interactions by adopting proper adaptive laws. Based on the Lyapunov function method and Barbalat＇s lemma, the obtained result is analytically proved. A colored network coupled with chaotic Lorenz, Chen, and Lii systems is considered as a numerical example to illustrate the effectiveness of the proposed method.
文摘This paper proposes a hybrid technique for color image segmentation. First an input image is converted to the image of CIE L＊a＊b＊ color space. The color features ＂a＂ and ＂b＂ of CIE L^＊a^＊b^＊ are then fed into fuzzy C-means （FCM） clustering which is an unsupervised method. The labels obtained from the clustering method FCM are used as a target of the supervised feed forward neural network. The network is trained by the Levenberg-Marquardt back-propagation algorithm, and evaluates its performance using mean square error and regression analysis. The main issues of clustering methods are determining the number of clusters and cluster validity measures. This paper presents a method namely co-occurrence matrix based algorithm for finding the number of clusters and silhouette index values that are used for cluster validation. The proposed method is tested on various color images obtained from the Berkeley database. The segmentation results from the proposed method are validated and the classification accuracy is evaluated by the parameters sensitivity, specificity, and accuracy.
文摘Fashion color forecasting is one of the most important factors for fashion marketing and manufacturing. Several models have been applied by previous researchers to conduct fashion color forecasting. However, few convincing forecasting systems have been established. A prediction model for fashion color forecasting was established by applying an improved back propagation neural network (BPNN) model in this paper. Successive six-year fashion color palettes, released by INTERCOLOR, were used as learning information for the neural network to develop a reliable prediction model. Colors in the palettes were quantified by PANTONE color system. Additionally, performance of the established model was compared with other GM(1, 1) models. Results show that the improved BPNN model is suitable to predict future fashion color trend.
文摘The colorant formulation using artificial neural networks (ANN) was investigated in this study. A simple 3 -layer, input - hidden - output system was constructed for the recipe formulation of one - , two - , and three -dye mixtures. Comprehensive tests were carried out to explore the properties of a 3 - layer simple ANN systematically . These properties include number of neurons in the hidden layer, learning rate of the network, momentum factor of the network, as well as the number of epochs for the learning process. The tests show accurate results for one - and two - dye mixtures while less accurate but comparable results to conventional colorant formulation systems for three - dye mixtures. It is also found that the optimum values of the neural network parameters are important towards the accuracy of the colorant formulation.
基金supported by the National Natural Science Foundation of China (Grants Nos. 61072139,61072106,61203303,61003198,61272279,and 61003199)
文摘An evolutionary network driven by dynamics is studied and applied to the graph coloring problem. From an initial structure, both the topology and the coupling weights evolve according to the dynamics. On the other hand, the dynamics of the network are determined by the topology and the coupling weights, so an interesting structure-dynamics co-evolutionary scheme appears. By providing two evolutionary strategies, a network described by the complement of a graph will evolve into several clusters of nodes according to their dynamics. The nodes in each cluster can be assigned the same color and nodes in different clusters assigned different colors. In this way, a co-evolution phenomenon is applied to the graph coloring problem. The proposed scheme is tested on several benchmark graphs for graph coloring.
基金the National Natural Science Foundation(60278022)
文摘A method of the forward operation of color appearance (from colorimetric attributes to color appearance attributes) using an artificial neural network (ANN) is presented The neural network model developed is a multilayer feedforward neural network model for predicting color appearance model (CAM). This method greatly decreased the mathematical computation in color appearance prediction. The error backed-propagation (BP) algorithm was applied in the training of the neural networks, and it was trained and tested by the LUTCHI color appearance datasets which are the most comprehensive one in testing color appearance model. CRT was selected as a typical example in experiment because it is usually used as self-luminous object in fact, and several ways for choosing training samples were included and compared each other. The testing results show that the color appearance prediction using artificial neural network is well consistent with visual evaluation.
文摘A CRT characterization method based on color appearance matching is presented. A matching between Munsell color chips and CRT charts was obtained in vision perceiver in typical office environment and viewing condition by recommending. And neural networks were utilized to accomplish the color space conversion from CIE standard color space to CRT device color space. The neural networks related the color space conversion and color reproduction of soft/hard-copy directly to the influence of the illuminance and viewing condition in vision perceiver. The average color difference of training samples is 3.06 and that of testing samples is 5.17. The experiment results indicated that the neural networks can satisfy the requirements for the color appearance of hard-copy reproduction in CRT.
文摘Systems using numerous cameras are emerging in many fields due to their ease of production and reduced cost, and one of the fields where they are expected to be used more actively in the near future is in image-based rendering （IBR）. Color correction between views is necessary to use multi-view systems in IBR to make audiences feel comfortable when views are switched or when a free viewpoint video is displayed. Color correction usually involves two steps： the first is to adjust camera parameters such as gain, brightness, and aperture before capture, and the second is to modify captured videos through image processing. This paper deals with the latter, which does not need a color pattern board. The proposed method uses scale invariant feature transform （SIFT） to detect correspondences, treats RGB channels independently, calculates lookup tables with an energy-minimization approach, and corrects captured video with these tables. The experimental results reveal that this approach works well.
文摘The new topological indices A x1 A x3 suggested in our laboratories were applied to the study of structure property relationships between color reagents and their color reactions with yttrium. The topological indices of twenty asymmetrical phosphone bisazo derivatives of chromotropic acid were calculated. The work shows that QSPR can be used as a novel aid to predict the molar absorptivities of color reactions and in the long term to be helpful tool in color reagent design. Multiple regression analysis and neural network were employed simultaneously in this study. The results demonstrated the feasibility and the effectiveness of the method.
文摘Improving routing algorithm performance not only leads to appreciate the quality of data transmission, but also increases the speed of data transfer. In this paper we propose a hybrid method which is a combination of traffic classification by the help of colored pheromones and helping ants method in the intermediate nodes. This combination increases the convergence speed and decreases the delay and Jitter in the network. Also we compare the obtained results with two known routing algorithms that are based on the ant colony.
基金Supported by the National Natural Science Foundation of China(No.71231004 and No.61004086)
文摘IEEE 802.11 based wireless mesh networks with directional antennas are expected to be a new promising technology and an economic approach for providing wireless broadband services in rural areas.In this paper,we discuss interference models and address how they can affect the design of channel assignment in rural mesh networks.We present a new channel assignment framework based on graph coloring for rural wireless mesh networks.The goal of the framework is to allow synchronously transmitting or receiving data from multiple neighbor links at the same time,and continuously doing full-duplex data transfer on every link,creating an efficient rural mesh network without interference.Channel assignment is shown to be NP-hard.We frame this channel allocation problem in terms of Adjacent Vertex Distinguishing Edge Coloring(AVDEC).Detailed assignment results on grid topology are presented and discussed.Furthermore,we design an algorithm.Finally,we evaluate the performance of the proposed algorithm through extensive simulations and show the algorithm is effective to the regular grid topologies,and the number of colors used by the algorithm is upper bounded by+1.Hence the algorithm guarantees that the number of channels available in standards such as IEEE802.11a is sufficient to have a valid AVDEC for many grid topologies.We also evaluate the proposed algorithm for arbitrary graphs.The algorithm provides a lower upper bound on the minimum number of channels to the AVDEC index channel assignment problem.
文摘图像去模糊需要在保留空间细节的同时确保高层次的上下文信息的平衡.针对模糊图像中的空间结构破坏,上下文信息扭曲以及RGB图像中的通道间强相关性造成的颜色不平衡等问题,本文提出一种基于YUV颜色空间和图卷积网络(GCN)的图像去模糊算法(YUVGCR).首先,设计了用于图像去模糊的YUV与RGB颜色空间转换算法,以解决RGB通道间强相关性的问题.然后,利用GCN可以将特征图转换为预生成图的顶点,对特征图进行图卷积,从而合成构建图结构的数据.通过这样做,可以隐式地将图拉普拉斯正则化应用于特征图,使其更加结构化.实验表明,YUVGCR的峰值信噪比(PSNR)为36.21 dB,比先进算法提高了2.93 d B.可视化去模糊结果可以看出,YUVGCR能产生更清晰的边缘和细节,图像去模糊的整体性能获得较大提升.
