共查询到20条相似文献，搜索用时 31 毫秒
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《Journal of The Franklin Institute》2022,359(16):9271-9295
In inertial navigation system and global navigation satellite system (INS/GNSS) integration, the practical stochastic measurement noise may be non-stationary heavy-tailed distribution due to outlier measurements induced by multipath and/or non-line-of-sight receptions of the original GNSS signals. To address the problem, a new switching Gaussian-heavy-tailed (SGHT) distribution is presented, which models the measurement noise with the help of switching between the Gaussian and the an existing heavy-tailed distribution. Then, utilizing two auxiliary parameters satisfying categorical and Bernoulli distributions respectively, we construct the SGHT distribution as a hierarchical Gaussian presentation. Furthermore, applying variational Bayesian inference, a novel SGHT distribution based robust Gaussian approximate filter is derived. Meanwhile, to reduce the computational complexity of the filtering process, an improved fixed-point iteration method is designed. Finally, the simulation of integrated navigation for an aircraft illustrates effectiveness and superiority of the proposed filter as compared the existing robust filters. 相似文献
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In this paper, we address the issue of sparse signal recovery in wireless sensor networks (WSNs) based on Bayesian learning. We first formulate a compressed sensing (CS)-based signal recovery problem for the detection of sparse event in WSNs. Then, from the perspective of energy saving and communication overhead reduction of the WSNs, we develop an optimal sensor selection algorithm by employing a lower-bound of the mean square error (MSE) for the MMSE estimator. To tackle the nonconvex difficulty of the optimum sensor selection problem, a convex relaxation is introduced to achieve a suboptimal solution. Both uncorrelated and correlated noises are considered and a low-complexity realization of the sensor selection algorithm is also suggested. Based on the selected subset of sensors, the sparse Bayesian learning (SBL) is utilized to reconstruct the sparse signal. Simulation results illustrate that our proposed approaches lead to a superior performance over the reference methods in comparison. 相似文献
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We propose in this paper an architecture for near-duplicate video detection based on: (i) index and query signature based structures integrating temporal and perceptual visual features and (ii) a matching framework computing the logical inference between index and query documents. As far as indexing is concerned, instead of concatenating low-level visual features in high-dimensional spaces which results in curse of dimensionality and redundancy issues, we adopt a perceptual symbolic representation based on color and texture concepts. For matching, we propose to instantiate a retrieval model based on logical inference through the coupling of an N-gram sliding window process and theoretically-sound lattice-based structures. The techniques we cover are robust and insensitive to general video editing and/or degradation, making it ideal for re-broadcasted video search. Experiments are carried out on large quantities of video data collected from the TRECVID 02, 03 and 04 collections and real-world video broadcasts recorded from two German TV stations. An empirical comparison over two state-of-the-art dynamic programming techniques is encouraging and demonstrates the advantage and feasibility of our method. 相似文献
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The linear canonical transform (LCT) has been shown to be a powerful tool for optics and signal processing. Many theories for this transform are already known, but the uniform sampling theorem, as well as the sampling rate conversion theory about arbitrary lattices sampling in the LCT domain are still to be determined. Focusing on these issues, this paper carefully investigates arbitrary lattices sampling, the sampling with separable matrices and nonseparable matrices, to obtain uniform sampling theorem and the sampling rate conversion theory in the LCT domain. Firstly, the spectral expression of the discrete-time signal sampled via arbitrary lattice is deduced in the LCT domain. Based on it we propose the alias-free sampling relationship between two matrices and present the perfect reconstruction expressions for bandlimited signals in the LCT domain. Secondly, for further research on discrete signals to obtain sampling rate conversion theory, we define the multidimensional discrete time linear canonical transform (MDTLCT), as well as the convolution for the MDTLCT. Thirdly, the formulas of multidimensional interpolation and decimation via integer matrices in the LCT domain are derived. Then, based on the results of interpolation and decimation, we make analyses of the sampling rate conversion via rational matrices in the LCT domain, including spectral analyses and the formulas in time domain. Finally, simulation results and the potential applications of the theories are also presented. 相似文献
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Wentao Bai Fan Guo Lei Chen Kuangrong Hao Biao Huang 《Journal of The Franklin Institute》2021,358(8):4546-4570
In traditional system identification methods, it is often assumed that the output data are corrupted by Gaussian white noise which is independent and identically distributed (i.i.d.). However, this assumption may lead to poor robustness since the noise characteristic often varies throughout the sampling process. In this work, output measurements affected by switching Gaussian noise are considered. In addition, a Markov chain model is utilized to describe the multi-mode behavior of the noises. Meanwhile, the collected data are usually incomplete in practice. Taking these circumstances into account, a new algorithm for Gaussian process regression (GPR) with switching noise mode and missing data is introduced. The parameters of the model are estimated by expectation maximization (EM) algorithm via conjugate gradient (CG) method. Two numerical examples along with a continuous stirred tank reactor simulation are employed to verify the effectiveness of the proposed algorithm. The superior performance is demonstrated by comparing the proposed algorithm with other existing relevant methods. 相似文献
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《Journal of The Franklin Institute》2002,339(6-7):499-520
In this paper we are concerned with the problems of (1) tracking or estimating the unknown, time-varying instantaneous frequency (IF) of a chirp signal from a multi-component signal (we assume our multi-component signal to be formed of additive chirp signals, disjoint in the time–frequency domain, and Gaussian noise) and (2) reconstructing a specific chirp signal based on the estimate of its IF found at (1). The algorithm we developed is based on a previously proposed method adapted now for the case of multi-component signals. It combines an adaptive smoothing procedure with a noise resistant Fourier filter to generate an algorithm with an extremely fine frequency resolution. The method is non-parametric, that is, we assume no prior knowledge about the form of the time-varying IF of the chirp or about the chirp itself. We demonstrate how the method works on simulated data and compare its performance to other presently used procedures. 相似文献
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《Information processing & management》2022,59(4):102949
This paper proposes a new method for semi-supervised clustering of data that only contains pairwise relational information. Specifically, our method simultaneously learns two similarity matrices in feature space and label space, in which similarity matrix in feature space learned by adopting adaptive neighbor strategy while another one obtained through tactful label propagation approach. Moreover, the above two learned matrices explore the local structure (i.e., learned from feature space) and global structure (i.e., learned from label space) of data respectively. Furthermore, most of the existing clustering methods do not fully consider the graph structure, they can not achieve the optimal clustering performance. Therefore, our method forcibly divides the data into c clusters by adding a low rank restriction on the graphical Laplacian matrix. Finally, a restriction of alignment between two similarity matrices is imposed and all items are combined into a unified framework, and an iterative optimization strategy is leveraged to solve the proposed model. Experiments in practical data show that our method has achieved brilliant performance compared with some other state-of-the-art methods. 相似文献
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Peiliang Xu 《Journal of The Franklin Institute》2021,358(7):4077-4102
Akaike’s Bayesian information criterion (ABIC) has been widely used in inverse ill-posed problems. Little has been done to investigate its statistical aspects. We present an alternative derivation of the marginal distribution of measurements for ABIC under the assumption of normal distributions and show that the principle of ABIC is to statistically estimate the variances of measurements and prior data by maximizing the marginal distribution of measurements. The determination of the regularization parameter with ABIC is essentially equivalent to estimating the relative weighting between measurements and prior data. We prove that ABIC theoretically would produce a biased estimate of the variance of measurements. Since the prior mean is generally unknown but arbitrarily treated as zero in inverse ill-posed problems, ABIC is shown to fail to produce any reasonable estimate for the prior variance. Although ABIC is constructed under the Bayesian framework, it essentially plays more or less the same role as biased regularization from the frequentist’s point of view. ABIC error evaluation cannot be performed under the Bayesian framework but should be more appropriately done with the frequentist’s standpoint in terms of mean squared errors. ABIC is sensitive to prior distributions. In the case of non-informative prior distribution, ABIC leads to the conventional weighted least squares (LS) estimate of parameters and cannot be used to solve inverse ill-posed problems. It is not linked to the regularization parameter but only straightforwardly produces an unbiased estimator for the noise level of measurements, which is only applicable numerically for well-posed problems but not for inverse ill-posed problems. Numerical simulated examples are used to demonstrate the statistical performances of ABIC. 相似文献
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目的：探讨PBL教学模式下超微结构病理学考核方法的改革。方法：以泸州医学院2011级本科检验专业学生为研究对象,分为PBL（Prob lem-based learning）教学组和SBL（Subject -based learning）教学组。从问卷调查、综述撰写、期末传统的考试成绩三方面综合评价两种教学效果与质量。结果：问卷调查结果显示,PBL教学增加学习兴趣、学习积极性、课堂气氛活跃度等,同时也增加了学习压力;综述考核显示,PBL教学组优于SBL教学组。而期末考试成绩两组无明显区别。结论：若需尽可能全面评估PBL教学模式的教学效果和质量,势必进行考核方法改革。 相似文献
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《Journal of The Franklin Institute》2023,360(9):6162-6193
A matrix-based framework for the modeling, analysis and dynamics of Bayesian games are presented using the semi-tensor product of matrices. Static Bayesian games are considered first. A new conversion of Bayesian games is proposed, which is called an action-type conversion. Matrix expressions are obtained for Harsanyi, Selten, and action-type conversions, respectively. Certain properties are obtained, including two kinds of Bayesian Nash equilibria. Then the verification of Bayesian potential games is considered, which is proved to test the solvability of corresponding linear equations equivalently. Finally, the dynamics of evolutionary Bayesian games are considered. Two learning rules for Bayesian potential games are proposed, which are type-based myopic best response adjustment and logit response rule, respectively. Markovian dynamic equations are obtained for the proposed strategy updating rules and convergence is proved. 相似文献
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20世纪中叶以来,随着计算机的诞生及其对科学与社会日渐显现的影响力,离散数学的思想和方法迅速发展,展现出了更为多样和充满活力的知识形态。离散数学的知识创新具有典型的数学范式革命性。作为对微积分范式的一种突破,离散数学超越了传统数学的知识界线,展现出在数学本体论、认识论与方法论上的新的哲学特征。与计算机与信息科学的发展相得益彰,离散数学范式具有离散化、算法化、计算性、复杂性以及与科学更为紧密的交互性等显著的当代科学革命特征,并显现出学科知识群与复杂性科学等独特的意蕴。 相似文献
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《Journal of The Franklin Institute》2018,355(18):9245-9270
This paper deals with noise detection and threshold free on-line denoising procedure for discrete scanning probe microscopy (SPM) surface images using wavelets. In this sense, the proposed denoising procedure works without thresholds for the localisation of noise, as well for the stop criterium of the algorithm. In particular, a proposition which states a constructive structural property of the wavelets tree with respect to a defined seminorm has been proven for a special technical case. Using orthogonal wavelets, it is possible to obtain an efficient localisation of noise and as a consequence a denoising of the measured signal. An on-line denoising algorithm, which is based upon the discrete wavelet transform (DWT), is proposed to detect unavoidable measured noise in the acquired data. With the help of a seminorm the noise of a signal is defined as an incoherent part of a measured signal and it is possible to rearrange the wavelet basis which can illuminate the differences between its coherent and incoherent part. In effect, the procedure looks for the subspaces consisting of wavelet packets characterised either by small or opposing components in the wavelet domain. Taking real measurements the effectiveness of the proposed denoising algorithm is validated and compared with Gaussian FIR- and Median filter. The proposed method was built using the free wavelet toolboxes from the WaveLab 850 library of the Stanford University (USA). 相似文献
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《Journal of The Franklin Institute》2022,359(15):8243-8264
In this paper, the balanced truncation method is investigated for discrete time-delay systems. We show that the energy associated with the system controllability and observability can be characterized via the delay Lyapunov matrices, similar to the case of continuous time-delay systems. Then, we balance the system via a coordinate transformation in order to retain the delay structure of systems naturally. In this way, the balanced truncation method is conducted to obtain structure-preserving reduced models. Further, we provide an efficient process to compute a low-rank approximation to delay Lyapunov matrices based on the equivalent expression of discrete time-delay systems, which enables an approximate but fast execution of the proposed method. The stability of reduced models is also discussed in the paper. Finally, numerical examples are simulated to verify the feasibility and efficiency of the proposed method. 相似文献
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贝叶斯网络(Bayesian Networks)是人工智能和数据挖掘领域中对不确定性问题进行推理和数据分析的一种工具,贝叶斯网络在人力资源中的应用也非常广,基于贝叶斯网络,分析人力资源管理中的主要因素,提出人力资源管理的贝叶斯网络构造方法,构建贝叶斯网络模型。 相似文献
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The general problem of root-clustering and root-distribution of a polynomial in a certain region Γ in the complex plane has been investigated in this paper. The region Γ is general and includes all the previously investigated regions. For the root-clustering problem, it is shown that by using a certain transformation, the necessary and sufficient condition can be represented either in terms of positive definite (p.d.) or positive innerwise (p.i.) matrices. The entries in these matrices are rational functions of the coefficients of the polynomial. The connection between p.d. and p.i. matrices is established in terms of matrix multiplication. 相似文献
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Iti Chaturvedi Edoardo Ragusa Paolo Gastaldo Rodolfo Zunino Erik Cambria 《Journal of The Franklin Institute》2018,355(4):1780-1797
Subjectivity detection is a task of natural language processing that aims to remove ‘factual’ or ‘neutral’ content, i.e., objective text that does not contain any opinion, from online product reviews. Such a pre-processing step is crucial to increase the accuracy of sentiment analysis systems, as these are usually optimized for the binary classification task of distinguishing between positive and negative content. In this paper, we extend the extreme learning machine (ELM) paradigm to a novel framework that exploits the features of both Bayesian networks and fuzzy recurrent neural networks to perform subjectivity detection. In particular, Bayesian networks are used to build a network of connections among the hidden neurons of the conventional ELM configuration in order to capture dependencies in high-dimensional data. Next, a fuzzy recurrent neural network inherits the overall structure generated by the Bayesian networks to model temporal features in the predictor. Experimental results confirmed the ability of the proposed framework to deal with standard subjectivity detection problems and also proved its capacity to address portability across languages in translation tasks. 相似文献
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基于贝叶斯网络的创新策源能力影响机制研究 《科学学研究》2021,39(10):1897-1907
创新策源能力是国家高质量发展的本质要求,是应对国际挑战的战略选择。基于创新策源能力的相关研究和贝叶斯网络基本原理,构建了创新策源能力影响机制贝叶斯网络模型,运用数学推理、算法简化和算例分析,通过改变贝叶斯网络中初始节点先验概率和中间节点条件概率,对创新策源能力多元化、复杂化、不确定影响因素的动态变化状态进行了模拟和仿真。研究结果表明：基于贝叶斯网络的创新策源能力研究,不仅将理论化、复杂化、系统化、结构化的创新策源能力问题转化成了可量化、可比较的数学问题,而且打破了传统研究影响机制问题单一、静态的局限,为创新策源能力影响机制的动态变化过程提供了理想的解决方案,为创新策源能力的培育、发展和提升提供了参考和支持。 相似文献