A “Dressed” Ensemble Kalman Filter Using the Hybrid Coordinate Ocean Model in the Pacific

The computational cost required by the Ensemble Kalman Filter （EnKF） is much larger than that of some simpler assimilation schemes, such as Optimal Interpolation （OI） or three-dimension variational as- similation （3DVAR）. Ensemble optimal interpolation （EnOI）, a crudely simplified implementation of EnKF, is sometimes used as a substitute in some oceanic applications and requires much less computational time than EnKF. In this paper, to compromise between computational cost and dynamic covariance, we use the idea of ＂dressing＂ a small size dynamical ensemble with a larger number of static ensembles in order to form an approximate dynamic covariance. The term ＂dressing＂ means that a dynamical ensemble seed from model runs is perturbed by adding the anomalies of some static ensembles. This dressing EnKF （DrEnKF for short） scheme is tested in assimilation of real altimetry data in the Pacific using the HYbrid Coordinate Ocean Model （HYCOM） over a four-year period. Ten dynamical ensemble seeds are each dressed by 10 static ensemble members selected from a 100-member static ensemble. Results are compared to two EnKF assimilation runs that use 10 and 100 dynamical ensemble members. Both temperature and salinity fields from the DrEnKF and the EnKF are compared to observations from Argo floats and an OI SST dataset. The results show that the DrEnKF and the 100-member EnKF yield similar root mean square errors （RMSE） at every model level. Error covariance matrices from the DrEnKF and the 100-member EnKF are also compared and show good agreement.

SAR image de-noising via grouping-based PCA and guided filter

A novel synthetic aperture radar(SAR)image de-noising method based on the local pixel grouping(LPG)principal component analysis(PCA)and guided filter is proposed.This method contains two steps.In the first step,we process the noisy image by coarse filters,which can suppress the speckle effectively.The original SAR image is transformed into the additive noise model by logarithmic transform with deviation correction.Then,we use the pixel and its nearest neighbors as a vector to select training samples from the local window by LPG based on the block similar matching.The LPG method ensures that only the similar sample patches are used in the local statistical calculation of PCA transform estimation,so that the local features of the image can be well preserved after coefficients shrinkage in the PCA domain.In the second step,we do the guided filtering which can effectively eliminate small artifacts left over from the coarse filtering.Experimental results of simulated and real SAR images show that the proposed method outstrips the state-of-the-art image de-noising methods in the peak signalto-noise ratio(PSNR),the structural similarity(SSIM)index and the equivalent number of looks(ENLs),and is of perceived image quality.

Current control for a shunt hybrid active power filter using recursive integral PI

This paper presents a current control method for a shunt hybrid active power filter （HAPF） using recursive integral PI algorithm. The method improves the performance of the HAPF system by reducing the influence of detection accuracy, time delay of instruction current calculation and phase displacement of output filter. Fuzzy logic based set-point weighing algorithm is combined in the control scheme to enhance its robustness and anti-interference ability. The proposed algorithm is easy to implement for engineering applications and easy to compute. Experiment results have verified the validity of the proposed controller. Furthermore, the proposed recursive integral PI algorithm can also be applied in the control of periodic current as in AC drivers.

Application of S-transform threshold filtering in Anhui experiment airgun sounding data de-noising

As a relatively new method of processing non-stationary signal with high time-frequency resolution, S transform can be used to analyze the time-frequency characteristics of seismic signals. It has the following characteristics: its time-frequency resolution corresponding to the signal frequency, reversible inverse transform, basic wavelet that does not have to meet the permit conditions. We combined the threshold method, proposed the S-transform threshold filtering on the basis of S transform timefrequency filtering, and processed airgun seismic records from temporary stations in "Yangtze Program"(the Anhui experiment). Compared with the results of the bandpass filtering, the S transform threshold filtering can improve the signal to noise ratio(SNR) of seismic waves and provide effective help for first arrival pickup and accurate travel time. The first arrival wave seismic phase can be traced farther continuously, and the Pm seismic phase in the subsequent zone is also highlighted.

Multi-sensor Hybrid Fusion Algorithm Based on Adaptive Square-root Cubature Kalman Filter

处于正常操作条件，一个常规方形根的求容积法 Kalman 过滤器(SRCKF ) 给足够地好的评价结果。然而，如果大小不是可靠的， SRCKF 可以给不精密的结果并且到时间分叉。这研究与过滤器获得修正介绍一个适应 SRCKF 算法因为测量的盒子失灵。由建议一个切换的标准，一个最佳的过滤器根据测量质量从适应、常规的 SRCKF 被选择。一个分系统软差错察觉算法与过滤器剩余被造。利用一个清楚的分系统差错系数，有缺点的分系统由于系统重建被孤立。以便改进多传感器系统的性能，一个混合熔化算法基于适应 SRCKF 被介绍。状态和错误协变性矩阵被 priori 熔化估计也预言，并且被分系统的预言并且估计的信息更新。建议算法被用于容器动态放系统模拟。他们与正常 SRCKF 和本地评价相比是加权的熔化算法。模拟结果证明介绍适应 SRCKF 改进分系统过滤的坚韧性，并且混合熔化算法有更好的表演。模拟验证建议算法的有效性。

Sliding Mode Controller for Three-Phase Hybrid Active Power Filter with Photovoltaic Application

This paper presents a new three-phase hybrid active power filter configuration that interconnects a passive high-pass filter in parallel with an active power filter and a photovoltaic system. The proposed configuration can improves the filtering performance of the conventional active power filter, as well as simultaneously supply the power from the photovoltaic arrays to the load and utility. This paper will describe the proposed hybrid active power filter control using sliding mode with photovoltaic system. The proposed technique effectively filters harmonics under 1 kHz but also higher frequency to achieve wideband harmonics compensation. The THD of source current is reduced from 30.09% to 1.95%. The result indicates that the sliding mode controller can track the reference signals and have good dynamic characteristics.

Contribution to Harmonic Depollution Control by the Use of Adaptive Hybrid Filter Type TLC: Case of Control by Modulated Hysteresis

In this article, we propose a topology of a TLC-HAPF power filter as a harmonic compensator for an optimization of the pollution control of electrical networks. This filter consists of an active part and a passive part in order to reduce or limit switching losses during current injection into networks thanks to its TLC module. This topology also provides solutions dynamic performance issues, resonance and lack of compensation capacity for imbalance cases. It also offers a greater range of compensation than conventional active models which do not offer as well as an intermediate circuit voltage in the order of 105 V to 109 V relatively lower than others models (600 v). A modulated hysteresis control of this topology is therefore also developed in this article and allows to obtain a network analysis on the three phases at three levels: source side, load side, and finally at the connection of the filter to the network, allowing to specify for these different positions the value of the current spectrum and its THD at this well-defined moment.

A Hybrid De-Noising Method on LASCA Images of Blood Vessels

A de-noising approach is proposed that based on the combination of wiener filtering, nonlinear filtering and wavelet fusion, which de-noise the LASCA (LAser Speckle Contrast Analysis) image of blood vessels in Small Animals. The approach first performs laser spectral contrast analysis on brain blood flow in rats, get their spatial and temporal contrast images. Then, a de-noising filtering method is proposed to deal with noise in LASCA. The image restoration is achieved by applying the proposed admixture filtering, and the subjective estimation and objective estimation are given to the de-noising images. As our experimental results shown, the proposed method provides clearer subjective sense and improved to over 25 db for PSNR.

Preparation and Optical Patterning of Organic-Inorganic Hybrid Color-Filter Films Using Latent Pigments by Utilizing Photo-Acid-Generator and Microwave Irradiation

Preparation and photo-patterning characteristics of organic-inorganic hybrid thin film containing latent pigment by using photo-acid-generator (PAG) and microwave irradiation have been investigated. The acrylic thin film modified with methoxysilane containing PAG was formed on a glass substrate and irradiated with ultraviolet rays to promote sol-gel reaction by catalytic action of acid which was generated from PAG. And then the film was hardened with microwave irradiation, yielding organic-inorganic hybrid polymer film having hardness, highly transparency and strong adhesion with a glass substrate. Since this reaction only occurred in the optically (UV) irradiated regions, by exploiting the difference between the adhesivenesses of these regions photo-irradiated through photomask with a glass substrate, it was possible to form a patterned film with pitch of 100 to 50 μm by a simple lift-off method. A pigment-containing film using latent pigments (with subtractive three primary colors of coloring materials) and a patterned film were prepared, and it was possible to make these films multi-colored by varying the mixing ratio of the pigments. This multi-colored film-preparation method is effective for simply and efficiently forming a color-filter film by applying optical and microwave irradiation.

Research on hybrid power filter of 6 kV power grid in coal mine

Studied the harmonic control of the 6 kV power grid in a coal mine substation.Taking harmonic suppression and reactive power compensation into account, and complyingwith the economic and efficient technical line of the smart grid, a new hybrid activefilter was proposed and applied to the power grid in the coal mine with the advantagessuch as large capacity, low cost and low loss.In order to improve detection speed and reducethe succeeding errors to improve the filtering performance of the active power filter,the DFT (Discrete Fourier Transform) sliding window algorithm based on coordinatetransformation and improved hysteresis control method was proposed.The Matlab simulationresults show that the hybrid active filter is satisfactory, can improve the grid powerfactor and can meet the requirements of improving the power quality in the coal mine.

Effects of main factors on remedying northern landscaping water by hybrid ecological filter

Natural zeolite and coal cinder were layered as main packing medium of the ecological filter instead of traditional filling to remedy the static lake water in Northern China.The ecological filter was running in a combined upward and downward flow mode.Dynamic experiments were carried out to study the effects of retention time and ambient temperature on pollutants' removal efficiency of the hybrid ecological filter.The function of plant was also studied by contrast test.It is showed that the removal efficiencies of NH4+-N and TP are increased when the retention time is changed from 1 h to 2 h and 4 h,but the removal efficiency of TN is decreased,the removal efficiency of NH4+-N is increased from 91.5% to 98% and that of TP is increased from 31.8% to 52.5%.When the temperature declines,the temporal removal efficiency of NH4+-N is reduced,but the removal efficiency of 24 h and 48 h is remained.The removal efficiency of TP after 24 h and 48 h is decreased when the temperature declines evidently.The retention time plays an important role in NH4+-N and TP removal,and the ambient temperature is significant for TP removal.The plant favors for TP and organic matter removal but has little effect on TN removal.

De-Noising Brain MRI Images by Mixing Concatenation and Residual Learning(MCR)

Brain magnetic resonance images(MRI)are used to diagnose the different diseases of the brain,such as swelling and tumor detection.The quality of the brain MR images is degraded by different noises,usually salt&pepper and Gaussian noises,which are added to the MR images during the acquisition process.In the presence of these noises,medical experts are facing problems in diagnosing diseases from noisy brain MR images.Therefore,we have proposed a de-noising method by mixing concatenation,and residual deep learning techniques called the MCR de-noising method.Our proposed MCR method is to eliminate salt&pepper and gaussian noises as much as possible from the brain MRI images.The MCR method has been trained and tested on the noise quantity levels 2%to 20%for both salt&pepper and gaussian noise.The experiments have been done on publically available brain MRI image datasets,which can easily be accessible in the experiments and result section.The Structure Similarity Index Measure(SSIM)and Peak Signal-to-Noise Ratio(PSNR)calculate the similarity score between the denoised images by the proposed MCR method and the original clean images.Also,the Mean Squared Error(MSE)measures the error or difference between generated denoised and the original images.The proposed MCR denoising method has a 0.9763 SSIM score,84.3182 PSNR,and 0.0004 MSE for salt&pepper noise;similarly,0.7402 SSIM score,72.7601 PSNR,and 0.0041 MSE for Gaussian noise at the highest level of 20%noise.In the end,we have compared the MCR method with the state-of-the-art de-noising filters such as median and wiener de-noising filters.

Decoupling control and zero dynamics stabilization for shunt hybrid active power filter

An inverse system method based optimal control strategy was proposed for the shunt hybrid active power filter(SHAPF)to enhance its harmonic elimination performance.Based on the inverse system method,the d-axis and q-axis current dynamics of the SHAPF system were decoupled and linearized into two pseudolinear subsystems.Then,an optimal feedback controller was designed for the pseudolinear system,and the stability condition of the resulting zero dynamics was presented.Under the control strategy,the current dynamics can asymptotically converge to their reference states and the zero dynamics can be bounded.Simulation results show that the proposed control strategy is robust against load variations and system parameter mismatches,its steady-state performance is better than that of the traditional linear control strategy.

OPTIMAL SMOOTHING FOR MICROPHONE ARRAY POST-FILTERING UNDER A COMBINED DETERMINISTIC-STOCHASTIC HYBRID MODEL

This paper shows the importance of the optimal smoothing scheme in Microphone Array Post-Filtering(MAPF) under a combined Deterministic-Stochastic Hybrid Model(DSHM).We reveal that some of the well-known MAPF algorithms may cause serious speech distortion without using the optimal smoothing scheme,which is resulted from oversmoothing the raw periodogram over time.Using a minimum conditional mean square error criterion,we derive the optimal smoothing factor under the DSHM,where the Deterministic-to-Stochastic-Ratio(DSR) and the stationarity determine the value of the optimal smoothing factor.The optimal smoothing scheme is applied to the Tran-sient-Beam-to-Reference-Ratio(TBRR)-based MAPF algorithm and experimental results show its better performance in terms of both the Log-Spectral Distance(LSD) and the Perceptual Evaluation of Speech Quality(PESQ).

Refinement of Enhanced Speech Using Hybrid-Median Filter and Harmonic Regeneration Approach

This study proposes a post-processor to improve the harmonic structure of a vowel in an enhanced speech, enabling the speech quality to be improved. Initially, a speech enhancement algorithm is employed to reduce the background noise for a noisy speech. Hence the enhanced speech is post-processed by a hybrid-median filter to reduce the musical effect of residual noise. Since the harmonic spectra are impacted by background noise and a speech enhancement process, the quality of a vowel is deteriorated. A harmonic regenerated method is developed to improve the quality of post-processed speech. Experimental results show that the proposed method can improve the quality of post-processed speech by adequately regenerating harmonic spectra.

基于情境感知和序列模式挖掘的气象学习资源推荐算法

随着互联网的快速发展,气象部门职工作为学习者可以获得的学习资源得到极大丰富。信息超载导致检索合适的在线学习资源时遇到了困难;学习者在不同学习环境和序列访问模式上也有不同的学习需求。但是,现有的推荐系统,如基于内容的推荐和协同过滤,没有结合学习者的情境和序列访问模式,推荐结果准确度不高。本文提出了一种结合情境感知、序列模式挖掘和协同过滤算法的混合推荐算法来为学习者推荐学习资源。混合推荐算法中,情境感知被用来整合学习者的情境信息,如知识水平和学习目标;序列模式挖掘被用来对网络日志进行挖掘,发现学习者的序列访问模式;协同过滤被用来根据学习者的情境数据和序列访问模式为目标学习者计算预测并生成建议。实验和应用效果表明,该混合推荐算法推荐的质量和准确性方面优于其他推荐算法。

基于主动式阻尼的混合式步进电机转速振荡抑制控制

混合式步进电机因其特殊的机械结构导致自身阻尼极小,在实际运行过程中会发生振荡过大,甚至失步的问题。为提高混合式步进电机的控制品质,提出一种基于主动式阻尼的步进电机转速振荡抑制方法。首先,将电机模型转化至同步旋转dq坐标系,将电流i_d控制恒为额定电流,利用位置误差和速度误差调节电流i_q生成瞬时转矩,抑制电机运行时存在的振荡现象。其次,为实现电机闭环反馈控制,提出一种将同步频率提取滤波器(SFF)与三阶锁相环(PLL~3rd)相结合的无传感器控制方法。SFF可以滤除反电动势信号中的高次谐波,PLL~3rd能消除转速变化过程中的稳态误差。实验证明,该方法有效抑制了步进电机运行过程中的振荡现象,提升了电机的运行品质。

基于容忍因子的近似最近邻混合查询算法

近似最近邻搜索(ANNS)是计算机领域中一种重要的高效相似度搜索技术,可用于在大规模数据集中进行快速信息检索。随着人们对高精度信息检索的需求不断增长,同时使用结构化信息和非结构化信息进行混合查询的方式也得到了广泛应用。然而,基于近邻图的过滤贪心算法在混合查询时可能会因结构化约束条件的影响导致连通性降低,进而损害搜索精度。为此,提出了一种基于容忍因子的过滤贪心算法,通过容忍因子控制不满足结构化约束条件的顶点参与路由,在不改变索引结构的前提下维持原有近邻图的连通性,克服了结构化约束条件对检索精度的负面影响。实验结果证明,新算法可以在不同结构化约束强度下实现ANNS的高精度搜索,同时保持检索效率。该研究解决了基于近邻图的ANNS在混合查询场景中的问题,为大规模数据集的快速混合查询信息检索提供了一种有效的解决方案。

一种使用多Filter初始化GA种群的混合特征选择模型

特征选择已经是高维数据处理尤其是模式识别领域中的一个关键问题.提出一种混合特征选择模型用于从潜在的相关特征中选择那些最重要的特征.该模型包括两部分:filter部分与wrapper部分.在filter部分,4种不同的Filter方法分别对候选特征进行独立排序,在融合后进一步生成综合特征排序,综合排序随后产生遗传算法(GA)的初始种群.在wrapper部分,GA算法根据神经网络的分类准确率对个体(特征子集)进行评价,以便于搜索到最优的特征子集.测试结果表明,该模型不仅能有效地减少特征子集的大小,而且还可以进一步提高分类识别的准确率和效果.