针对传统高斯分布估计算法(Gaussian estimation of distribution algorithms,GEDAs)中变量方差减小速度快、概率密度椭球体(Probability density ellipsoid,PDE)的长轴与目标函数的改进方向相垂直,从而导致算法搜索效率低、容易早熟收...针对传统高斯分布估计算法(Gaussian estimation of distribution algorithms,GEDAs)中变量方差减小速度快、概率密度椭球体(Probability density ellipsoid,PDE)的长轴与目标函数的改进方向相垂直,从而导致算法搜索效率低、容易早熟收敛这一问题,提出一种基于一般二阶混合矩的高斯分布估计算法.该算法利用加权的优秀样本预估高斯均值,并根据沿目标函数的改进方向偏移后的均值来估计协方差矩阵.理论和数值分析表明,这一简单操作可以在不增大算法计算量的前提下自适应地调整概率密度椭球体的位置、大小和长轴方向,提高算法的搜索效率.在14个标准函数上对所提算法进行了测试,由统计出的Cohen's d效应量指标可知该算法的全局寻优能力强于传统高斯分布估计算法;与当前先进的粒子群算法、差分进化算法相比,所提算法可以在相同的函数评价次数内获得9个函数的显著优解.展开更多
This paper proposes a spatially denoising algorithm using filtering-based noise estimation for an image corrupted by Gaussian noise.The proposed algorithm consists of two stages:estimation and elimination of noise den...This paper proposes a spatially denoising algorithm using filtering-based noise estimation for an image corrupted by Gaussian noise.The proposed algorithm consists of two stages:estimation and elimination of noise density.To adaptively deal with variety of the noise amount,a noisy input image is firstly filtered by a lowpass filter.Standard deviation of the noise is computed from different images between the noisy input and its filtered image.In addition,a modified Gaussian noise removal filter based on the local statistics such as local weighted mean,local weighted activity and local maximum is used to control the degree of noise suppression.Experiments show the effectiveness of the proposed algorithm.展开更多
In this paper, an evolutionary recursive Bayesian estimation algorithm is presented, which incorporates the latest observation with a new proposal distribution, and the posterior state density is represented by a Gaus...In this paper, an evolutionary recursive Bayesian estimation algorithm is presented, which incorporates the latest observation with a new proposal distribution, and the posterior state density is represented by a Gaussian mixture model that is recovered from the weighted particle set of the measurement update step by means of a weighted expectation-maximization algorithm. This step replaces the resampling stage needed by most particle filters and relieves the effect caused by sample impoverishment. A nonlinear tracking problem shows that this new approach outperforms other related particle filters.展开更多
This paper developed an improved combinatorial method called the best chromosome clone plus younger generation chromosome prepotency genetic algorithm （BCC-YGCP-GA） to evaluate aquifer parameters. This method is bas...This paper developed an improved combinatorial method called the best chromosome clone plus younger generation chromosome prepotency genetic algorithm （BCC-YGCP-GA） to evaluate aquifer parameters. This method is based on a decimal simple genetic algorithm （SGA）. A synthetic example for unsteady-state flow in a two-dimensional, inhomogeneous, confined aquifer containing three hydraulically distinct zones, is used to develop data to test the model. The simulation utilizes SGA and BCC-YGCP-GA coupled to the finite element method to identify the mean zonal hydraulic conductivities, and storage coefficients of the three-compartment model. For this geometrically simple model, used as a prototype of more complex systems, the SGA does not reach convergence within 100 generations. Conversely, the convergence rate of the BCC-YGCD-GA model is very fast. The objective function value calculated by BCC-YGCD-GA is reduced to 1/1 O00th of the starting value within 100 generations, and the hydraulic conductivity and storage of three zones are within a few percent of the “true” values of the ideal model, highlighting the power of the method for aquifer parameterization.展开更多
High-Order Cumulants （HOC） and cross-correlation was combined to suppress the Gaussian color noises and the tin-related noises in real applications. The cross-HOC TOA estimation model was developed based on the diag...High-Order Cumulants （HOC） and cross-correlation was combined to suppress the Gaussian color noises and the tin-related noises in real applications. The cross-HOC TOA estimation model was developed based on the diagonal slice of the forth-cross-cumu-lant. The eigen analysis was carried out, and the eigea noise space and the eigen signal space was achieved. Then the Frequency Domain TOA estimation algorithm based on Cross-HOC was developed. Different simulation experiments were carried out to draw out the conclusions.展开更多
文摘针对传统高斯分布估计算法(Gaussian estimation of distribution algorithms,GEDAs)中变量方差减小速度快、概率密度椭球体(Probability density ellipsoid,PDE)的长轴与目标函数的改进方向相垂直,从而导致算法搜索效率低、容易早熟收敛这一问题,提出一种基于一般二阶混合矩的高斯分布估计算法.该算法利用加权的优秀样本预估高斯均值,并根据沿目标函数的改进方向偏移后的均值来估计协方差矩阵.理论和数值分析表明,这一简单操作可以在不增大算法计算量的前提下自适应地调整概率密度椭球体的位置、大小和长轴方向,提高算法的搜索效率.在14个标准函数上对所提算法进行了测试,由统计出的Cohen's d效应量指标可知该算法的全局寻优能力强于传统高斯分布估计算法;与当前先进的粒子群算法、差分进化算法相比,所提算法可以在相同的函数评价次数内获得9个函数的显著优解.
基金supported by the Korea Science and Engineering Foundation(KOSEF) grant fund by the Korea Govern-ment(MEST)(No.2011-0000148)the Ministry of Knowledge Economy,Korea under the Infor mation Technology Research Center support programsupervised by the National IT Industry Promotion Agency(NIPA-2011-C1090-1121-0010)
文摘This paper proposes a spatially denoising algorithm using filtering-based noise estimation for an image corrupted by Gaussian noise.The proposed algorithm consists of two stages:estimation and elimination of noise density.To adaptively deal with variety of the noise amount,a noisy input image is firstly filtered by a lowpass filter.Standard deviation of the noise is computed from different images between the noisy input and its filtered image.In addition,a modified Gaussian noise removal filter based on the local statistics such as local weighted mean,local weighted activity and local maximum is used to control the degree of noise suppression.Experiments show the effectiveness of the proposed algorithm.
基金Sponsored by the National Security Major Basic Research Project of China(Grant No.973 -61334)
文摘In this paper, an evolutionary recursive Bayesian estimation algorithm is presented, which incorporates the latest observation with a new proposal distribution, and the posterior state density is represented by a Gaussian mixture model that is recovered from the weighted particle set of the measurement update step by means of a weighted expectation-maximization algorithm. This step replaces the resampling stage needed by most particle filters and relieves the effect caused by sample impoverishment. A nonlinear tracking problem shows that this new approach outperforms other related particle filters.
文摘This paper developed an improved combinatorial method called the best chromosome clone plus younger generation chromosome prepotency genetic algorithm （BCC-YGCP-GA） to evaluate aquifer parameters. This method is based on a decimal simple genetic algorithm （SGA）. A synthetic example for unsteady-state flow in a two-dimensional, inhomogeneous, confined aquifer containing three hydraulically distinct zones, is used to develop data to test the model. The simulation utilizes SGA and BCC-YGCP-GA coupled to the finite element method to identify the mean zonal hydraulic conductivities, and storage coefficients of the three-compartment model. For this geometrically simple model, used as a prototype of more complex systems, the SGA does not reach convergence within 100 generations. Conversely, the convergence rate of the BCC-YGCD-GA model is very fast. The objective function value calculated by BCC-YGCD-GA is reduced to 1/1 O00th of the starting value within 100 generations, and the hydraulic conductivity and storage of three zones are within a few percent of the “true” values of the ideal model, highlighting the power of the method for aquifer parameterization.
文摘High-Order Cumulants （HOC） and cross-correlation was combined to suppress the Gaussian color noises and the tin-related noises in real applications. The cross-HOC TOA estimation model was developed based on the diagonal slice of the forth-cross-cumu-lant. The eigen analysis was carried out, and the eigea noise space and the eigen signal space was achieved. Then the Frequency Domain TOA estimation algorithm based on Cross-HOC was developed. Different simulation experiments were carried out to draw out the conclusions.
