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THE LINEAR KERNEL OF BOOLEAN FUNCTIONS AND PARTIALLY-BENT FUNCTIONS 被引量:1
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作者 WANG Jianyu (Department of Mathematics, Nankai University, Tianiin 300071, China) 《Systems Science and Mathematical Sciences》 SCIE EI CSCD 1997年第1期6-11,共6页
We will give the definition of the linear kernel of boolean functions and prove that, by a reversible linear transformation, any linear structure boolean function can be transformed into a boolean function which is li... We will give the definition of the linear kernel of boolean functions and prove that, by a reversible linear transformation, any linear structure boolean function can be transformed into a boolean function which is linear to some variables, is non-relative to some variables and is of non-linear structure to other variables; any Partially-Bent Function can be transformed into a boolean function which is linear to some variables, is nonrelativeto some variables ans is bent to other variables. We will also discuss the Walsh Spectral Characterization of Partially-Bent Functions. 展开更多
关键词 Partially-Bent FUNCTIONS WALSH spectral linear kernel
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Linear Discriminant Analysis and Kernel Vector Quantization for Mandarin Digits Recognition
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作者 赵军辉 谢湘 匡镜明 《Journal of Beijing Institute of Technology》 EI CAS 2004年第4期385-388,共4页
Linear discriminant analysis and kernel vector quantization are integrated into vector quantization based speech recognition system for improving the recognition accuracy of Mandarin digits. These techniques increase ... Linear discriminant analysis and kernel vector quantization are integrated into vector quantization based speech recognition system for improving the recognition accuracy of Mandarin digits. These techniques increase the class separability and optimize the clustering procedure. Speaker-dependent (SD) and speaker-independent (SI) experiments are performed to evaluate the performance of the proposed method. The experiment results show that the proposed method is capable of reaching the word error rate of 3.76% in SD case and 6.60 % in SI case. Such a system can be suitable for being embedded in personal digital assistant(PDA), mobile phone and so on to perform voice controlling such as digit dialing, calculating, etc. 展开更多
关键词 linear discriminant analysis kernel vector quantization speech recognition
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Interior-Point Algorithm for Linear Optimization Based on a New Kernel Function 被引量:2
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作者 CHEN Donghai ZHANG Mingwang LI Weihua 《Wuhan University Journal of Natural Sciences》 CAS 2012年第1期12-18,共7页
In this paper, we design a primal-dual interior-point algorithm for linear optimization. Search directions and proximity function are proposed based on a new kernel function which includes neither growth term nor barr... In this paper, we design a primal-dual interior-point algorithm for linear optimization. Search directions and proximity function are proposed based on a new kernel function which includes neither growth term nor barrier term. Iteration bounds both for large-and small-update methods are derived, namely, O(nlog(n/c)) and O(√nlog(n/ε)). This new kernel function has simple algebraic expression and the proximity function has not been used before. Analogous to the classical logarithmic kernel function, our complexity analysis is easier than the other pri- mal-dual interior-point methods based on logarithmic barrier functions and recent kernel functions. 展开更多
关键词 linear optimization interior-point algorithms pri- mal-dual methods kernel function polynomial complexity
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Interior-point algorithm based on general kernel function for monotone linear complementarity problem
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作者 刘勇 白延琴 《Journal of Shanghai University(English Edition)》 CAS 2009年第2期95-101,共7页
A polynomial interior-point algorithm is presented for monotone linear complementarity problem (MLCP) based on a class of kernel functions with the general barrier term, which are called general kernel functions. Un... A polynomial interior-point algorithm is presented for monotone linear complementarity problem (MLCP) based on a class of kernel functions with the general barrier term, which are called general kernel functions. Under the mild conditions for the barrier term, the complexity bound of algorithm in terms of such kernel function and its derivatives is obtained. The approach is actually an extension of the existing work which only used the specific kernel functions for the MLCP. 展开更多
关键词 monotone linear complementarity problem (MLCP) interior-point method kernel function polynomial complexity
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Numerical Solution of Nonlinear Mixed Integral Equation with a Generalized Cauchy Kernel
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作者 Fatheah Ahmed Hendi Manal Mohamed Al-Qarni 《Applied Mathematics》 2017年第2期209-214,共6页
In this article, we present approximate solution of the two-dimensional singular nonlinear mixed Volterra-Fredholm integral equations (V-FIE), which is deduced by using new strategy (combined Laplace homotopy perturba... In this article, we present approximate solution of the two-dimensional singular nonlinear mixed Volterra-Fredholm integral equations (V-FIE), which is deduced by using new strategy (combined Laplace homotopy perturbation method (LHPM)). Here we consider the V-FIE with Cauchy kernel. Solved examples illustrate that the proposed strategy is powerful, effective and very simple. 展开更多
关键词 Singular Integral Equation linear and NONlinear V-FIE HOMOTOPY Perturbation Method (HPM) CAUCHY kernel
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Comparison between Adomian’s Decomposition Method and Toeplitz Matrix Method for Solving Linear Mixed Integral Equation with Hilbert Kernel
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作者 Fatheah Ahmed Hendi Manal Mohamed Al-Qarni 《American Journal of Computational Mathematics》 2016年第2期177-183,共7页
This paper proposes the combined Laplace-Adomian decomposition method (LADM) for solution two dimensional linear mixed integral equations of type Volterra-Fredholm with Hilbert kernel. Comparison of the obtained resul... This paper proposes the combined Laplace-Adomian decomposition method (LADM) for solution two dimensional linear mixed integral equations of type Volterra-Fredholm with Hilbert kernel. Comparison of the obtained results with those obtained by the Toeplitz matrix method (TMM) demonstrates that the proposed technique is powerful and simple. 展开更多
关键词 Singular Integral Equation linear Volterra-Fredholm Integral Equation Adomian Decomposition Method Hilbert kernel
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Numerical Treatment of Nonlinear Volterra-Fredholm Integral Equation with a Generalized Singular Kernel
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作者 Fatheah Ahmed Hendi Manal Mohamed Al-Qarni 《American Journal of Computational Mathematics》 2016年第3期245-250,共7页
In the paper, the approximate solution for the two-dimensional linear and nonlinear Volterra-Fredholm integral equation (V-FIE) with singular kernel by utilizing the combined Laplace-Adomian decomposition method (LADM... In the paper, the approximate solution for the two-dimensional linear and nonlinear Volterra-Fredholm integral equation (V-FIE) with singular kernel by utilizing the combined Laplace-Adomian decomposition method (LADM) was studied. This technique is a convergent series from easily computable components. Four examples are exhibited, when the kernel takes Carleman and logarithmic forms. Numerical results uncover that the method is efficient and high accurate. 展开更多
关键词 Singular Integral Equation linear and Nonlinear V-FIE Adomian Decomposition Method (ADM) Carleman kernel Logarithmic kernel
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A novel LS-SVM control for unknown nonlinear systems with application to complex forging process 被引量:1
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作者 FAN Bin LU Xin-jiang HUANG Ming-hui 《Journal of Central South University》 SCIE EI CAS CSCD 2017年第11期2524-2531,共8页
A novel LS-SVM control method is proposed for general unknown nonlinear systems. A linear kernel LS-SVM model is firstly developed for input/output(I/O) approximation. The LS-SVM control law is then derived directly f... A novel LS-SVM control method is proposed for general unknown nonlinear systems. A linear kernel LS-SVM model is firstly developed for input/output(I/O) approximation. The LS-SVM control law is then derived directly from this developed model without any approximation and assumption. It further proves that the control error is fully equal to the LS-SVM modeling error. This means that a desirable control performance can be achieved because the LS-SVM has been proven to have an outstanding modeling ability in the previous studies. Case studies finally demonstrate the effectiveness of the proposed LS-SVM control approach. 展开更多
关键词 unknown system inverse control input/output approximation LS-SVM control linear kernel
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基于LDA+kernel-KNNFLC的语音情感识别方法 被引量:8
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作者 张昕然 查诚 +2 位作者 徐新洲 宋鹏 赵力 《东南大学学报(自然科学版)》 EI CAS CSCD 北大核心 2015年第1期5-11,共7页
结合K近邻、核学习方法、特征线重心法和LDA算法,提出了用于情感识别的LDA+kernel-KNNFLC方法.首先针对先验样本特征造成的计算量庞大问题,采用重心准则学习样本距离,改进了核学习的K近邻方法;然后加入LDA对情感特征向量进行优化,在避... 结合K近邻、核学习方法、特征线重心法和LDA算法,提出了用于情感识别的LDA+kernel-KNNFLC方法.首先针对先验样本特征造成的计算量庞大问题,采用重心准则学习样本距离,改进了核学习的K近邻方法;然后加入LDA对情感特征向量进行优化,在避免维度冗余的情况下,更好地保证了情感信息识别的稳定性.最后,通过对特征空间再学习,结合LDA的kernel-KNNFLC方法优化了情感特征向量的类间区分度,适合于语音情感识别.对包含120维全局统计特征的语音情感数据库进行仿真实验,对降维方案、情感分类器和维度参数进行了多组对比分析.结果表明,LDA+kernel-KNNFLC方法在同等条件下性能提升效果最显著. 展开更多
关键词 语音情感识别 K近邻 核学习 特征重心线 线性判别分析
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LINEAR SINGULAR INTEGRAL EQUATION ON DOMAINS COMPOSED BY BALLS 被引量:3
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作者 黄玉笙 林良裕 《Acta Mathematica Scientia》 SCIE CSCD 2006年第1期145-151,共7页
For domains composed by balls in C^n, this paper studies the boundary behaviour of Cauchy type integrals with discrete holomorphic kernels and the corresponding linear singular integral equation on each piece of smoot... For domains composed by balls in C^n, this paper studies the boundary behaviour of Cauchy type integrals with discrete holomorphic kernels and the corresponding linear singular integral equation on each piece of smooth lower dimensional edges on the boundary of the domain. 展开更多
关键词 Domains composed by balls discrete kernel linear singular integral equation
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ESTIMATORS AND SOME BEHAVIORS FORA PARTIALLY LINEAR MODEL WITH CENSORED DATA 被引量:2
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作者 陈平 《Acta Mathematica Scientia》 SCIE CSCD 1999年第3期321-331,共11页
This paper considers the local linear regression estimators for partially linear model with censored data. Which have some nice large-sample behaviors and are easy to implement. By many simulation runs, the author als... This paper considers the local linear regression estimators for partially linear model with censored data. Which have some nice large-sample behaviors and are easy to implement. By many simulation runs, the author also found that the estimators show remarkable in the small sample case yet. 展开更多
关键词 partial linear model censored data local linear smoothing cross-validation kernel estimator
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ESTIMATION FOR THE AYMPTOTIC VARIANCE OF PARAMETRIC ESTIMATES IN PARTIAL LINEAR MODEL WITH CENSORED DATA 被引量:2
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作者 秦更生 蔡雷 《Acta Mathematica Scientia》 SCIE CSCD 1996年第2期192-208,共17页
Consider tile partial linear model Y=Xβ+ g(T) + e. Wilers Y is at risk of being censored from the right, g is an unknown smoothing function on [0,1], β is a 1-dimensional parameter to be estimated and e is an unobse... Consider tile partial linear model Y=Xβ+ g(T) + e. Wilers Y is at risk of being censored from the right, g is an unknown smoothing function on [0,1], β is a 1-dimensional parameter to be estimated and e is an unobserved error. In Ref[1,2], it wes proved that the estimator for the asymptotic variance of βn(βn) is consistent. In this paper, we establish the limit distribution and the law of the iterated logarithm for,En, and obtain the convergest rates for En and the strong uniform convergent rates for gn(gn). 展开更多
关键词 Partial linear model Censored data kernel method Asymptotic normality Thc law of the iterated logarithm.
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Real-Valued Discrete Gabor Transform of Linear Time-Varying Systems: Exact Representation and Approximation
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作者 陶亮 罗斌 《Journal of Electronic Science and Technology of China》 2005年第1期1-5,共5页
An efficient algorithm for the representation and approximation of linear time-varying systems is presented via the fast real-valued discrete Gabor transform. Compared with the existing algorithm based on the traditio... An efficient algorithm for the representation and approximation of linear time-varying systems is presented via the fast real-valued discrete Gabor transform. Compared with the existing algorithm based on the traditional complex-valued discrete Gabor transform, the proposed algorithm runs faster, can more easily be implemented in software or hardware, and leads to a more compact representation. Simulation results are given for demonstration. 展开更多
关键词 Gabor transforms real-valued discrete Gabor transforms kernel representation linear time-varying systems
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基于FDTRP-ALDCNN的小样本轴承故障诊断方法
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作者 王娜 刘佳林 王子从 《铁道科学与工程学报》 北大核心 2025年第9期4271-4283,共13页
针对滚动轴承在小样本条件下诊断精度低的问题,提出一种基于频域无阈值递归图与自适应线性可变卷积神经网络(frequency domain thresholdless recurrence plot-adaptive linear deformable convolutional neural network,FDTRP-ALDCNN)... 针对滚动轴承在小样本条件下诊断精度低的问题,提出一种基于频域无阈值递归图与自适应线性可变卷积神经网络(frequency domain thresholdless recurrence plot-adaptive linear deformable convolutional neural network,FDTRP-ALDCNN)的滚动轴承故障诊断方法。首先,使用快速傅里叶变换(fast fourier transform,FFT)将一维时域信号转为频域信号,并与无阈值递归图(thresholdless recurrence plot,TRP)相结合,以有效构建初始特征,提高模型输入质量;其次,采用线性可变卷积核(linear deformable convolutional kernel,LDConv)替换卷积神经网络中方形卷积核,从而能够根据采样数据的分布来调整卷积核形状,准确获取空间信息中的关键特征,提高小样本数据的利用率;再次,设计自适应交叉熵(adaptive cross entropy,ACE)损失函数,根据样本分类损失自适应调整分类器对难分与易分样本的拟合程度,增强难分样本损失在整体分类损失中的显著性,进一步提高小样本下的模型诊断精度;最后,采用CWRU滚动轴承数据集对所提方法进行3组仿真验证。对比仿真的结果表明,所提模型在不同小样本数量下均有较高的诊断准确率,最高可达到99.82%。而对2组不平衡数据集的泛化性分析可知,本模型的诊断准确率分别达到98.56%与99.3%,泛化能力优于其他模型,且具有良好的稳定性。并通过消融实验验证了FFT、LDConv与ACE损失函数对提高故障诊断精度的有效性。综上所述,所提方法能够有效诊断出小样本轴承故障,具有较高的实际应用价值。 展开更多
关键词 故障诊断 小样本 无阈值递归图 线性可变卷积核 卷积神经网络 交叉熵损失函数
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基于KLDA-IDBO-BP的装甲车发动机故障诊断 被引量:5
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作者 李英顺 于昂 +2 位作者 李茂 贺喆 刘师铭 《兵工学报》 北大核心 2025年第3期105-113,共9页
润滑油在发动机中发挥作用时携带着大量关于发动机的状态信息,能够对发动机产生的故障进行表征,可利用其对发动机进行故障诊断。以某型装甲车辆发动机为研究对象,提出一种基于核线性判别和改进的蜣螂优化算法优化反向传播(Back Propagat... 润滑油在发动机中发挥作用时携带着大量关于发动机的状态信息,能够对发动机产生的故障进行表征,可利用其对发动机进行故障诊断。以某型装甲车辆发动机为研究对象,提出一种基于核线性判别和改进的蜣螂优化算法优化反向传播(Back Propagation,BP)神经网络的故障诊断方法。对获取的润滑油数据通过核线性判别分析进行降维处理,降维后的数据作为BP神经网络的输入,通过引入最优拉丁超立方、权重因子以及Levy飞行策略对蜣螂优化算法进行改进,进一步对BP神经网络的关键参数进行优化,建立故障诊断模型,实现对测试数据的故障预测。实验结果验证了新方法在进行故障诊断预测方面的有效性,为装甲车辆发动机的维护和修理提供了科学依据。 展开更多
关键词 润滑油信息 发动机 故障诊断 蜣螂优化算法 反向传播神经网络 核线性判别分析
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基于缓存数据重用的稀疏矩阵向量乘序列优化
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作者 徐传福 邱昊中 车永刚 《计算机研究与发展》 北大核心 2025年第6期1434-1442,共9页
稀疏线性方程组求解等高性能计算应用常常涉及稀疏矩阵向量乘(SpMV)序列Ax,A2x,…,Asx的计算.上述SpMV序列操作又称为稀疏矩阵幂函数(matrix power kernel,MPK).由于MPK执行多次SpMV且稀疏矩阵保持不变,在缓存(cache)中重用稀疏矩阵,可... 稀疏线性方程组求解等高性能计算应用常常涉及稀疏矩阵向量乘(SpMV)序列Ax,A2x,…,Asx的计算.上述SpMV序列操作又称为稀疏矩阵幂函数(matrix power kernel,MPK).由于MPK执行多次SpMV且稀疏矩阵保持不变,在缓存(cache)中重用稀疏矩阵,可避免每次执行SpMV均从主存加载A,从而缓解SpMV访存受限问题,提升MPK性能.但缓存数据重用会导致相邻SpMV操作之间的数据依赖,现有MPK优化多针对单次SpMV调用,或在实现数据重用时引入过多额外开销.提出了缓存感知的MPK(cache-awareMPK,Ca-MPK),基于稀疏矩阵的依赖图,设计了体系结构感知的递归划分方法,将依赖图划分为适合缓存大小的子图/子矩阵,通过构建分割子图解耦数据依赖,根据特定顺序在子矩阵上调度执行SpMV,实现缓存数据重用.测试结果表明,Ca-MPK相对于Intel OneMKL库和最新MPK实现,平均性能提升分别多达约1.57倍和1.40倍. 展开更多
关键词 稀疏矩阵向量乘 矩阵幂函数 缓存数据重用 数据依赖 稀疏线性方程组求解
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自适应核动态潜变量算法及输电线路极端冰冻灾害预警模型
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作者 刘潇潇 李鹏 +1 位作者 张璇 彭庆军 《云南大学学报(自然科学版)》 北大核心 2025年第2期244-254,共11页
针对输电线路极端冰冻灾害预警模型中小概率样本不易获取以及在提取特征动态关系时难以在线学习的问题,提出一种自适应核动态潜变量算法及输电线路极端冰冻灾害预警模型.首先,该模型使用正常数据构建基于核动态潜变量(kernel dynamic la... 针对输电线路极端冰冻灾害预警模型中小概率样本不易获取以及在提取特征动态关系时难以在线学习的问题,提出一种自适应核动态潜变量算法及输电线路极端冰冻灾害预警模型.首先,该模型使用正常数据构建基于核动态潜变量(kernel dynamic latent variable,KDLV)的离线模型,并获得到统计限T_(lim)^(2);然后,引入模型自适应更新准则对近似线性依靠算法(approximate linear dependence,ALD)进行改进,利用改进的ALD算法更新统计限T_(lim)^(2),从而自适应提取动态潜变量特征;最后,利用KDLV模型计算测试集数据的统计量T_(lim)^(2),以测试集数据统计量T_(lim)^(2)是否超过统计限T_(lim)^(2)作为判断标准.运用滇东北某输电线路覆冰数据进行实验验证.相较于动态潜变量、KDLV、动态内部主元分析及时序近邻保持嵌入方法,提出的方法灾害预警正确率最高、漏报率最低、误报率最低. 展开更多
关键词 输电线路极端冰冻灾害 核动态潜变量 近似线性依靠 小概率样本 自适应预警
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关于线性变换像空间与核空间的注记
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作者 林丽仁 徐运阁 陈媛 《高等数学研究》 2025年第1期39-41,49,共4页
设σ是数域F上n维线性空间V的线性变换,本文探讨了线性空间V可以分解成线性变换σ的像空间与核空间的直和的充要条件,并从线性变换的矩阵表示的角度理清了线性空间V、像空间与核空间之间的关系;最后,我们证明V总能分解成线性变换σ~n的... 设σ是数域F上n维线性空间V的线性变换,本文探讨了线性空间V可以分解成线性变换σ的像空间与核空间的直和的充要条件,并从线性变换的矩阵表示的角度理清了线性空间V、像空间与核空间之间的关系;最后,我们证明V总能分解成线性变换σ~n的像空间与核空间的直和. 展开更多
关键词 线性变换 像空间 核空间 直和
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边缘敏感的超像素与混合核函数聚类的遥感影像分割算法
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作者 付主俊 《测绘与空间地理信息》 2025年第12期94-97,101,共5页
针对模糊C均值聚类算法在遥感影像分割中存在边缘信息丢失、分割结果不稳定等问题,提出边缘敏感的超像素与混合核函数聚类的遥感影像分割算法。首先,将边缘强度因子引入简单线性迭代聚类算法中,充分利用影像边缘特征,获取影像过分割的... 针对模糊C均值聚类算法在遥感影像分割中存在边缘信息丢失、分割结果不稳定等问题,提出边缘敏感的超像素与混合核函数聚类的遥感影像分割算法。首先,将边缘强度因子引入简单线性迭代聚类算法中,充分利用影像边缘特征,获取影像过分割的超像素;其次,通过粒子群算法获取过分割超像素的初始聚类中心;最后,利用马氏距离的混合核函数改进欧氏距离的单一高斯核函数,将数据映射到高维特征空间进行核模糊C均值聚类处理,实现高分辨率遥感影像的精确分割。试验结果表明,该方法可以有效保留地物边界信息,提高高分辨率遥感影像分割精度。 展开更多
关键词 边缘强度因子 简单线性聚类 混合核函数 模糊C均值聚类
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基于核密度的线性惩罚样条光滑方法
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作者 刘雨 晏梅 《统计与决策》 北大核心 2025年第14期47-52,共6页
惩罚样条光滑方法是一种用于数据拟合和光滑的非参数统计方法,通过在样条函数的拟合过程中引入惩罚约束来减少噪声和降低不规则性。为了达到最佳的光滑效果,选择最优的惩罚项、惩罚参数和样条节点仍然是需要关注的问题。针对这些问题,... 惩罚样条光滑方法是一种用于数据拟合和光滑的非参数统计方法,通过在样条函数的拟合过程中引入惩罚约束来减少噪声和降低不规则性。为了达到最佳的光滑效果,选择最优的惩罚项、惩罚参数和样条节点仍然是需要关注的问题。针对这些问题,文章基于岭回归和核密度技术提出了一种新的惩罚样条光滑方法。新方法利用样条节点处的核密度构造惩罚矩阵,并使用岭回归的范数作为样条系数的惩罚项;此外,新方法先使用逐步向前方法选择最优的样条节点,再使用基于矩阵分解的广义交叉验证(GCV)准则快速选择最优的惩罚参数,从而极大地提高了新方法的运算速度。通过模拟实验可知,新方法对于各类复杂的回归模型都能有较好的拟合与预测效果;另外,对于不连续回归模型以及解释变量是偏态分布的情形,新方法仍有较好的预测效果,并且优于其他回归方法。 展开更多
关键词 ReLU 线性惩罚样条 非参数回归 节点选择 核密度 光滑方法
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