Target Parameters Estimation of Frequency Diverse Array based on Preprocessing l1SVD Algorithm

基于预处理l1SVD算法的频控阵目标参数估计，廖艳苹，潘越，针对l1范数奇异值分解算法在面对数据量过大，算法效率降低的问题，本文提出了基于预处理l1SVD算法。该方法是基于L型频控阵阵列结构
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TDOA estimation algorithm based on generalized cyclic correntropy
20181012SUMMARY This paper mainly discusses the timedifferenceofarrival (TDOA) estimation problem of digital modulation signal under impulsive noise and cochannel interference environment. Since the conventional TDOA estimation algorithms based on the secondorder cyclic statistics degenerated severely in impulsive noise and the TDOA estimation algorithms based on correntropy are out of work in cochannel interference, a novel robust signalselective algorithm based on the generalized cyclic correntropy is proposed, which can suppress both impulsive noise and cochannel interference. Theoretical derivation and simulation results demonstrate the effectiveness and robustness of the proposed algorithm. key words: Alphastable distribution, impulsive noise, Cyclic correntropy,TDOA, Cochannel interference.
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High Bandwidth Sensorless Algorithm for AC Machines Based on Squarewave Type
20190917This paper describes a new control algorithm which can enhance the dynamics of a sensorless control system and gives a precise sensorless control performance. Instead of the conventional sinusoidaltype voltage injection, a squarewavetype voltage injection incorporated with the associated signal processing method is proposed in this paper. As a result, the error signal can be calculated without lowpass filters and time delays, and the position estimation performance can be enhanced. Using the proposed method, the performance of the sensorless control can be enhanced; the bandwidth of the current controller was enhanced up to 250 Hz, and that of the speed controller was up to 50 Hz.
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Estimation of Dependences Based on Empirical Data
20091028Twentyfive years have passed since the publication of the Russian version of the book Estimation of Dependencies Based on Empirical Data (EDBED for short). Twentyfive years is a long period of time. During these years many things have happened. Looking back, one can see how rapidly life and technology have changed, and how slow and difficult it is to change the theoretical foundation of the technology and its philosophy. I pursued two goals writing this Afterword: to update the technical results presented in EDBED (the easy goal) and to describe a general picture of how the new ideas developed over these years (a much more difficult goal). The picture which I would like to present is a very personal (and therefore very biased) account of the development of one particular branch of science, Empirical Inference Science. Such accounts usually are not included in the content of technical publications. I have followed this rule in all of my previous books. But this time I would like to violate it for the following reasons. First of all, for me EDBED is the important milestone in the development of empirical inference theory and I would like to explain why. Second, during these years, there were a lot of discussions between supporters of the new paradigm (now it is called the VC theory1) and the old one (classical statistics). Being involved in these discussions from the very beginning I feel that it is my obligation to describe the main events. The story related to the book, which I would like to tell, is the story of how it is difficult to overcome existing prejudices (both scientific and social), and how one should be careful when evaluating and interpreting new technical concepts. This story can be split into three parts that reflect three main ideas in the development of empirical inference science: from the pure technical (mathematical) elements of the theory to a new paradigm in the philosophy of generalization. The first part of the story, which describes the main technical concepts behind the new mathematical and philosophical paradigm, can be titled Realism and Instrumentalism: Classical Statistics and VC Theory In this part I try to explain why between 1960 and 1980 a new approach to empirical inference science was developed in contrast to the existing classical statistics approach developed between 1930 and 1960. The second part of the story is devoted to the rational justification of the new ideas of inference developed between 1980 and 2000. It can be titled Falsifiability and Parsimony: VC Dimension and the Number of Entities It describes why the concept of VC falsifiability is more relevant for predictive generalization problems than the classical concept of parsimony that is used both in classical philosophy and statistics. The third part of the story, which started in the 2000s can be titled Noninductive Methods of Inference: Direct Inference Instead of Generalization It deals with the ongoing attempts to construct new predictive methods (direct inference) based on the new philosophy that is relevant to a complex world, in contrast to the existing methods that were developed based on the classical philosophy introduced for a simple world. I wrote this Afterword with my students’ students in mind, those who just began their careers in science. To be successful they should learn something very important that is not easy to find in academic publications. In particular they should see the big picture: what is going on in the development of this science and in closely related branches of science in general (not only about some technical details). They also should know about the existence of very intense paradigm wars. They should understand that the remark of Cicero, “Among all features describing genius the most important is inner professional honesty”, is not about ethics but about an intellectual imperative. They should know that Albert Einstein’s observation about everyday scientific life that “Great spirits have always encountered violent opposition from mediocre minds,” is still true. Knowledge of these things can help them to make the right decisions and avoid the wrong ones. Therefore I wrote a fourth part to this Afterword that can be titled The Big Picture. This, however, is an extremely difficult subject. That is why it is wise to avoid it in technical books, and risky to discuss it commenting on some more or less recent events in the development of the science. Writing this Afterword was a difficult project for me and I was able to complete it in the way that it is written due to the strong support and help of my colleagues Mike Miller, David Waltz, Bernhard Sch¨olkopf, Leon Bottou, and Ilya Muchnik.
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ESPRITEstimation of Signal Parameters Via Rotational Invariance Techniques
20101117ESPRITEstimation of Signal Parameters Via Rotational Invariance Techniques， author：RICHARD ROY AND THOMAS KAILATH, FELLOW，IEEE
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State of charge estimation of LiFePO4 battery based on a gainclassifier observer
20210210State of charge estimation of LiFePO4 battery based on a gainclassifier observer
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Inverse synthetic aperture radar imaging of nonuniformly rotating target based on the parameters estimation of multicomponent quadratic frequencymodulated signals
20210207Inverse synthetic aperture radar imaging of nonuniformly rotating target based on the parameters estimation of multicomponent quadratic frequencymodulated signals
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基于多项式展开的两帧运动估计TwoFrame Motion Estimation Based on Polynomial Expansion
20171114基于多项式展开的两帧运动估计 翻译 TwoFrame Motion Estimation Based on Polynomial Expansion
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Online Estimation Method of Flotation PH based on Adaptive Multilevel Neural Network
20210210Online Estimation Method of Flotation PH based on Adaptive Multilevel Neural Network
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Vapnik大作第二版，Estimation of Dependences Based on Empirical Data(基于经验数据的依赖性估计)
20110322统计、模式识别方面的大牛Vapnik的经典作品：Estimation of Dependences Based on Empirical Data 2nd Edition(基于经验数据的依赖性估计 第二版)。 2006年重印，这里的文件是新加入的内容。
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RVFLNbased online adaptive semisupervised learning algorithm with application to product quality estimation of industrial processes
20210208RVFLNbased online adaptive semisupervised learning algorithm with application to product quality estimation of industrial processes
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UCSD 博士论文 Priors and Learning Based Methods for SuperResolution
20120619In this dissertation we propose priors and learning based methods for super resolution and other video processing applications. We also propose eﬃcient al gorithms for global motion estimation and projection on L1 ball under box con straints. We propose total subset variation (TSV), a convexity preserving general ization of total variation (TV) prior, for higher order clique MRF. A proposed diﬀerentiable approximation of the TSV prior makes it amenable for use in large images (e.g. 1080p). A generalization to vector valued data enables use of the TSV prior for color images and motion ﬁeld. A convex relaxation of subexponential distribution is proposed as a criterion to determine parameters of the optimiza tion problem resulting from the TSV prior. For superresolution application, ex periments show reconstruction error improvement in terms of PSNR as well as Structural Similarity (SSIM) with respect to TV and other methods. We also propose an image upscaling algorithm based on ν support vector regression. Working in the pixel domain, spatial neighborhood in the form of rect angular patches are used to determine the high resolution pixels at the center of the patch. Since, interpolation involves matching the test patch against a descrip tive subset of training patches (support vectors) to ﬁnd similar training patches which then have higher inﬂuence on the result of interpolation, the approach is inherently adaptive to local image content. We also investigate ν support vector xiiiregression for compression artifact reduction application. For global motion estimation application, we propose a fast and robust 2D aﬃne global motion estimation algorithm based on phasecorrelation in Fourier Mellin domain and robust least square model ﬁtting of sparse motion vector ﬁeld. Rotationscaletranslation (RST) approximation of aﬃne parameters is obtained at coarsest level of image pyramid, as opposed to only initial translation estimate [2] [3], thus ensuring convergence for much larger range of motions. Despite working at coarsest resolution level, use of subpixelaccurate phase correlation [4] provides suﬃciently accurate coarse estimates for subsequent reﬁnement stage of the algo rithm. Reﬁnement stage consists of RANSAC [5] based robust leastsquare model ﬁtting to sparse motion vector ﬁeld, estimated using blockbased subpixelaccurate phase correlation at randomly selected high activity regions in ﬁnest level of image pyramid. Resulting algorithm is very robust to outliers like foreground objects and ﬂat regions. Experimental results show proposed algorithm is capable of esti mating larger range of motions as compared to MPEG4 veriﬁcation model, while achieving a speedup of 200. A combination of priors for statistics of single frames of natural video and motion estimation between diﬀerent frames of video is essential for good perfor mance of any general video processing application.
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a noise estimation algorithm
20130320A noise estimation algorithm is proposed for highly non stationary noise environments. The noise estimate is updated by averaging the noisy speech power spectrum using a time and frequency dependent smoothing factor, which is adjusted based on signal presence probability in subbands. Signal presence is determined by computing the ratio of the noisy speech power spectrum to its local minimum, which is computed by averaging past values of the noisy speech power spectra with a lookahead factor. The local minimum estimation algorithm adapts very quickly to highly nonstationary noise environments. This was confirmed with formal listening tests that indicated that our noise estimation algorithm when integrated in speech enhancement was preferred over other noise estimation algorithms.
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Robust prognostics for state of health estimation of lithiumion batteries based on animproved PSOSVR model
20210211Robust prognostics for state of health estimation of lithiumion batteries based on animproved PSOSVR model
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Symbian操作系统开发经验
20090806Symbian OS是Symbian公司专为移动电话设备开发的操作系统。这是当前占市场份额最大的手机操作系统。Symbian公司最大的控股公司就是Nokia。 Symbian C++是Symbian OS最基本的编程语言。
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On Degeneracy of Optimizationbased State Estimation Problems.pdf
20200922LOAM SLAM中用于非线性优化的方法《On Degeneracy of Optimizationbased State Estimation Problems》，大家可以详细阅读，有需要的可以下载。同时可以参照博客https://blog.csdn.net/i_robots/article/details/108724606
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Fast Estimation of Gaussian Mixture Models for Image Segmentation
20150710利用高斯混合模型实现图像分割The ExpectationMaximization algorithmhas been classically used to find the maximum likelihood estimates of parameters in probabilistic models with unobserved data, for instance, mixture models. A key issue in such problems is the choice of the model complexity. The higher the number of components in the mixture, the higher will be the data likelihood, but also the higher will be the computational burden and data overfitting. In this work we propose a clustering method based on the expectation maximization algorithm that adapts online the number of components of a finite Gaussian mixture model from multivariate data. Or method estimates the number of components and their means and covariances sequentially, without requiring any careful initialization.
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Enhanced fourthpower algorithm for phase estimation with frequency separation in directdetection optical OFDM systems
20210205The optical orthogonal frequency division multiplexing (OFDM) signal is affected by impairments introduced by electrical filters and optical chromatic dispersion. An enhanced fourthpower algorithm for phase estimation with frequency separation is used to estimate and compensate the phase rotation of OFDM subcarriers. The performance of the proposed phase estimation algorithm is evaluated on a 4Gb/s OFDM signal at different frequencies. Experimental results using the proposed algorithm show a 1
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A state estimation Algorithm of power system based on the mixed measurement
20200127一种基于混合量测的电力系统状态估计算法，张恒，，本文针对电力系统中量测方式的多样性的现状，将SCADA系统采集的数据和其他方式下的注入功率量测量统一通过量测变换技术转化为等效�

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20192025年中国瓶装饮用水行业市场深度调研及前景趋势预测报告.pdf
20192025年中国瓶装饮用水行业市场深度调研及前景趋势预测报告.pdf

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20192025年中国团餐行业市场深度调研及前景趋势预测报告.pdf
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20202025年中国泵行业市场深度调研及发展战略研究报告.pdf
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