In this paper, a classification method based on Support Vector Machine (SVM) is given in the digital modulation signal classification. The second, fourth and sixth order cumulants of the received signals are used as c...In this paper, a classification method based on Support Vector Machine (SVM) is given in the digital modulation signal classification. The second, fourth and sixth order cumulants of the received signals are used as classification vectors firstly, then the kernel thought is used to map the feature vector to the high dimensional feature space and the optimum separating hyperplane is constructed in space to realize signal recognition. In order to build an effective and robust SVM classifier, the radial basis kernel function is selected, one against one or one against rest of multi-class classifier is designed, and method of parameter selection using cross- validation grid is adopted. Through the experiments it can be concluded that the classifier based on SVM has high performance and is more robust.展开更多
In the paper [Monotone countable paracompactness and maps to ordered topological vector spaces, Top. Appl., 2014, 169（3）： 51–70], Yamazaki initiated the study on maps with values into ordered topological vector sp...In the paper [Monotone countable paracompactness and maps to ordered topological vector spaces, Top. Appl., 2014, 169（3）： 51–70], Yamazaki initiated the study on maps with values into ordered topological vector spaces. Characterizations of monotonically countably paracompact spaces and some other spaces in terms of maps to ordered topological vector spaces were obtained. In this paper, following Yamazaki＇s method, we present some characterizations of stratifiable spaces and k-semi-stratifiable spaces in terms of maps with values into ordered topological vector spaces.展开更多
A great number of semi-analytical models, notably the representation of electromagnetic fields by integral equations are based on the second order vector potential (SOVP) formalism which introduces two scalar potentia...A great number of semi-analytical models, notably the representation of electromagnetic fields by integral equations are based on the second order vector potential (SOVP) formalism which introduces two scalar potentials in order to obtain analytical expressions of the electromagnetic fields from the two potentials. However, the scalar decomposition is often known for canonical coordinate systems. This paper aims in introducing a specific SOVP formulation dedicated to arbitrary non-orthogonal curvilinear coordinates systems. The electromagnetic field representation which is derived in this paper constitutes the key stone for the development of semi-analytical models for solving some eddy currents moelling problems and electromagnetic radiation problems considering at least two homogeneous media separated by a rough interface. This SOVP formulation is derived from the tensor formalism and Maxwell’s equations written in a non-orthogonal coordinates system adapted to a surface characterized by a 2D arbitrary aperiodic profile.展开更多
The stationary probability vectors of a second order Markov chain on the(n-1)-dimensional standard simplex are considered.In 2015,Li and Zhang gave a characterization of the second order Markov chain such that every v...The stationary probability vectors of a second order Markov chain on the(n-1)-dimensional standard simplex are considered.In 2015,Li and Zhang gave a characterization of the second order Markov chain such that every vector in the simplex is a stationary vector.A modification of the characterization is presented in the paper.Some sufficient conditions are derived for any facet of the simplex such that every vector of the facet is a stationary vector.展开更多
In this paper, we introduce the concept of a (weak) minimizer of order k for a nonsmooth vector optimization problem over cones. Generalized classes of higher-order cone-nonsmooth (F, ρ)-convex functions are introduc...In this paper, we introduce the concept of a (weak) minimizer of order k for a nonsmooth vector optimization problem over cones. Generalized classes of higher-order cone-nonsmooth (F, ρ)-convex functions are introduced and sufficient optimality results are proved involving these classes. Also, a unified dual is associated with the considered primal problem, and weak and strong duality results are established.展开更多
Mathematical morphology can process the binary and grayscale image successfully. This theory cannot be extended to the color image directly. In color space, a vector represents a pixel, so in order to compare vectors,...Mathematical morphology can process the binary and grayscale image successfully. This theory cannot be extended to the color image directly. In color space, a vector represents a pixel, so in order to compare vectors, vectoriel orderings must be defined first. This paper addresses the question of the extension of morphological operator to the case of color images. The proposed method used the order by bit mixing to replace the conditional order. Our order is based on a combination of reduced and bit mixing ordering of the underlying data. Additionally it is a total ordering. Since it not only solves the problems of false color generated by the marginal order but also those of multiple extrema generated by reduced order. The performance of the introduced operators is illustrated by means of different applications: color gradients for segmenting, image smoothing (noise suppression) by median filter operator and Laplacian operators. Examples of natural color images and synthetic color images are given. Experimental results show the improvement brought by this new method.展开更多
为应对复杂多变的未知环境对海洋航行器运动预测所造成的挑战,提出了一种融合级联滤波与误差触发支持向量回归(error-triggered support vector regression,ETSVR)的智能预测系统。首先,该系统基于移动平均滤波对原始数据进行预处理,以...为应对复杂多变的未知环境对海洋航行器运动预测所造成的挑战,提出了一种融合级联滤波与误差触发支持向量回归(error-triggered support vector regression,ETSVR)的智能预测系统。首先,该系统基于移动平均滤波对原始数据进行预处理,以剔除异常值并抑制高频噪声,为后续预测提供高质量的数据集;其次,引入二阶扩展卡尔曼滤波对系统状态进行精确估计,进一步增强数据的平稳度和可靠性;最后,设计ETSVR算法对处理后的高质量数据集进行学习,以构建海洋航行器的运动预测模型,实现精准运动预测,并借助误差触发机制提升系统的实时性与计算效率。基于湖试数据的实验结果表明,所提出的智能运动预测系统在多项误差指标上均显著优于传统的线性回归算法。例如,在侧向速度预测中,均方误差较线性回归算法降低约53.2%;在转艏角速度预测中,最大误差减少了约58.2%。这些结果表明,提出的级联滤波与ETSVR算法相结合的智能预测系统,能够显著提升海洋航行器在复杂未知环境中的运动预测精度,具有较好的应用前景和重要的研究意义。展开更多
文摘In this paper, a classification method based on Support Vector Machine (SVM) is given in the digital modulation signal classification. The second, fourth and sixth order cumulants of the received signals are used as classification vectors firstly, then the kernel thought is used to map the feature vector to the high dimensional feature space and the optimum separating hyperplane is constructed in space to realize signal recognition. In order to build an effective and robust SVM classifier, the radial basis kernel function is selected, one against one or one against rest of multi-class classifier is designed, and method of parameter selection using cross- validation grid is adopted. Through the experiments it can be concluded that the classifier based on SVM has high performance and is more robust.
基金Supported by the National Natural Science Foundation of China(Grant No.11401262)
文摘In the paper [Monotone countable paracompactness and maps to ordered topological vector spaces, Top. Appl., 2014, 169（3）： 51–70], Yamazaki initiated the study on maps with values into ordered topological vector spaces. Characterizations of monotonically countably paracompact spaces and some other spaces in terms of maps to ordered topological vector spaces were obtained. In this paper, following Yamazaki＇s method, we present some characterizations of stratifiable spaces and k-semi-stratifiable spaces in terms of maps with values into ordered topological vector spaces.
文摘A great number of semi-analytical models, notably the representation of electromagnetic fields by integral equations are based on the second order vector potential (SOVP) formalism which introduces two scalar potentials in order to obtain analytical expressions of the electromagnetic fields from the two potentials. However, the scalar decomposition is often known for canonical coordinate systems. This paper aims in introducing a specific SOVP formulation dedicated to arbitrary non-orthogonal curvilinear coordinates systems. The electromagnetic field representation which is derived in this paper constitutes the key stone for the development of semi-analytical models for solving some eddy currents moelling problems and electromagnetic radiation problems considering at least two homogeneous media separated by a rough interface. This SOVP formulation is derived from the tensor formalism and Maxwell’s equations written in a non-orthogonal coordinates system adapted to a surface characterized by a 2D arbitrary aperiodic profile.
基金National Natural Science Foundation of China(Nos.1167125811371086)
文摘The stationary probability vectors of a second order Markov chain on the(n-1)-dimensional standard simplex are considered.In 2015,Li and Zhang gave a characterization of the second order Markov chain such that every vector in the simplex is a stationary vector.A modification of the characterization is presented in the paper.Some sufficient conditions are derived for any facet of the simplex such that every vector of the facet is a stationary vector.
文摘In this paper, we introduce the concept of a (weak) minimizer of order k for a nonsmooth vector optimization problem over cones. Generalized classes of higher-order cone-nonsmooth (F, ρ)-convex functions are introduced and sufficient optimality results are proved involving these classes. Also, a unified dual is associated with the considered primal problem, and weak and strong duality results are established.
文摘Mathematical morphology can process the binary and grayscale image successfully. This theory cannot be extended to the color image directly. In color space, a vector represents a pixel, so in order to compare vectors, vectoriel orderings must be defined first. This paper addresses the question of the extension of morphological operator to the case of color images. The proposed method used the order by bit mixing to replace the conditional order. Our order is based on a combination of reduced and bit mixing ordering of the underlying data. Additionally it is a total ordering. Since it not only solves the problems of false color generated by the marginal order but also those of multiple extrema generated by reduced order. The performance of the introduced operators is illustrated by means of different applications: color gradients for segmenting, image smoothing (noise suppression) by median filter operator and Laplacian operators. Examples of natural color images and synthetic color images are given. Experimental results show the improvement brought by this new method.
文摘为应对复杂多变的未知环境对海洋航行器运动预测所造成的挑战,提出了一种融合级联滤波与误差触发支持向量回归(error-triggered support vector regression,ETSVR)的智能预测系统。首先,该系统基于移动平均滤波对原始数据进行预处理,以剔除异常值并抑制高频噪声,为后续预测提供高质量的数据集;其次,引入二阶扩展卡尔曼滤波对系统状态进行精确估计,进一步增强数据的平稳度和可靠性;最后,设计ETSVR算法对处理后的高质量数据集进行学习,以构建海洋航行器的运动预测模型,实现精准运动预测,并借助误差触发机制提升系统的实时性与计算效率。基于湖试数据的实验结果表明,所提出的智能运动预测系统在多项误差指标上均显著优于传统的线性回归算法。例如,在侧向速度预测中,均方误差较线性回归算法降低约53.2%;在转艏角速度预测中,最大误差减少了约58.2%。这些结果表明,提出的级联滤波与ETSVR算法相结合的智能预测系统,能够显著提升海洋航行器在复杂未知环境中的运动预测精度,具有较好的应用前景和重要的研究意义。
