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检索条件"主题词=Recursive algorithms"

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ORTHO-DIFFUSION DECOMPOSITIONS FOR FACE RECOGNITION FROM LOW QUALITY IMAGES

ORTHO-DIFFUSION DECOMPOSITIONS FOR FACE RECOGNITION FROM LOW...

引用

IEEE International Conference on Image Processing

作者： Sravan Gudivada Adrian G. Bors Department of Computer Science University of York

ISBN: (纸本)9781479983407

We propose a new approach for recognizing human from images of low quality. An ortho-diffusion decomposition is used on graph representations of images. This is implemented by a recursive algorithm in three steps on either the covariance matrix or on the correlation of the training set. The first stage consists of an orthonormal decomposition implemented through the modified Gram-Schmidt with pivoting the columns. The other two stages consists of the data reduction and diffusion on graph representations. The data reduction ensures that the most significant features are preserved and together with the diffusion step ensures robustness to a variety of data corruption factors. The proposed methodology produces a set of ortho-diffusion bases representing the quintessential information from the training data set. The resulting orhto-diffusion bases are used to model face images when considering low resolution and corruption by various noise distributions.

关键词： Gram-Schmidt algorithm Diffusion wavelets Robust face recognition Facial Recognition Graph representations images data reduction Face variance covariance matrix recursive algorithms vandalism corruption Ensure data corruption diffusion

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Hidden Markov Model Estimation-Based Q-learning for Partially Observable Markov Decision Process

Hidden Markov Model Estimation-Based Q-learning for Partiall...

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American Control Conference

作者： Hyung-Jin Yoon Donghwan Lee Naira Hovakimyan University of Illinois at Urbana-Champaign (UIUC) Urbana IL 61801 USA UIUC

ISBN: (纸本)9781538679012;9781538679265

The objective is to study an on-line Hidden Markov model (HMM) estimation-based Q-learning algorithm for partially observable Markov decision process (POMDP) on finite state and action sets. When the full state observation is available, Q-learning finds the optimal action-value function given the current action (Q-function). However, Q-learning can perform poorly when the full state observation is not available. In this paper, we formulate the POMDP estimation into a HMM estimation problem and propose a recursive algorithm to estimate both the POMDP parameter and Q-function concurrently. Also, we show that the POMDP estimation converges to a set of stationary points for the maximum likelihood estimate, and the Q-function estimation converges to a fixed point that satisfies the Bellman optimality equation weighted on the invariant distribution of the state belief determined by the HMM estimation process.

关键词： hidden Markov models learning (artificial intelligence) maximum likelihood estimation optimisation Hidden Markov models maximum likelihood estimation Markov chain Q FUNCTIONS recursive algorithms

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On the performance of balance factors of the dichromatic balanced trees for massive data

On the performance of balance factors of the dichromatic bal...

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2016 2nd International Conference on Electronics,Network and Computer Engineering(ICENCE 2016)

作者： Xiaodong WANG Daxin ZHU Fujian University of Technology Quanzhou Normal University

In this paper, we are interested in minimal number of red-nodes in a red-black tree. An O（nlogn） time dynamic programming algorithm is presented first for computing s（ n）, the smallest number of red internal nodes in a red-black tree on n keys. We then improve the algorithm to a new O（ n） time algorithm. Then the algorithm is improved further to some O（ logn）time recursive and nonrecursive algorithms. These improved algorithms finally led to a closed-form solution of s（ n）.

关键词： Balanced Trees recursive algorithms Closed-Form Solutions

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Estimation and Characteristic Analysis of Aggregated Generation of Geographically Distributed Wind Farms

Estimation and Characteristic Analysis of Aggregated Generat...

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IEEE Power and Energy Society General Meeting

作者： Jiang Wu Xiaohong Guan Xiaoxin Zhou Yuxun Zhou SKLMS Lab MOE KLINNS Lab and the Systems Engineering Institute Xian Jiaotong University China Electric Power Research Institute

ISBN: (纸本)9781457710001

A good understanding of the aggregated stochastic characteristics of available wind generation is very important for secured and economic system operation in market environment. This paper focus on estimating and analyzing the aggregated generation of geographically distributed wind farms. A dynamic system model is formulated to describe the relationship between atmospheric and near-surface wind fields of the individual wind farms. A recursive algorithm based on Kalman filter theory is developed to update the parameters from NWP and to estimate the generation of individual wind farms based on their geographical locations, the wind dynamics in atmosphere, and the initial temporal and spatial conditions of the wind fields. The stochastic characteristics of the total available wind generation can then be estimated as the aggregation of the individual generation estimation. The actual data validates the assertion that the aggregated wind generation of distributed wind farms is less volatile than that of a single wind farm.

关键词： Wind generation Kalman filter Dynamic system State estimation Numeric weather prediction Wind energy generation Wind farms Dynamic systems State estimation Kalman filters Kalman filter theory recursive algorithms Operating systems

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Latency-Aware Base Station Selection Scheme for Cellular-Connected UAVs

Latency-Aware Base Station Selection Scheme for Cellular-Con...

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IEEE Vehicular Technology Conference

作者： Yang Long Tao Yang Hui Feng Bo Hu Res. Center of Smart Networks & Syst. Fudan Univ. Shanghai China

ISBN: (纸本)9781538663592;9781538663585

Wireless communication system incorporating unmanned aerial vehicles (UAVs) has gained much popularity recently, especially in video transmission application. This paper investigates the base station (BS) selection scheme for cellular-connected UAVs that possess the function of video collection and streaming to BS for online decision in remote processing center. We aim to minimize the expected access latency while the throughput requirement is satisfied. To this end, a sequential BS selection scheme is proposed by designing an optimal transmission rate threshold for each candidate BS. Due to the mission-driven nature, the access rate varies as the UAV moves, so an effective average transmission rate rather than instantaneous transmission rate is considered. A recursive algorithm is proposed to obtain the rate thresholds which can be used to guide whether UAV should stop or continue measuring the links of the remaining candidate BSs. The proof of the optimality of this algorithm is given. Simulation results validate the effectiveness of the proposed scheme on access latency performance compared with conventional throughput-oriented scheme.

关键词： autonomous aerial vehicles cellular radio quality of service radio networks remotely operated vehicles Unmanned vehicles Unmanned Aerial Vehicle cellular radio Radio networks Quality of service Bahamas access rate remote processing drone honey bees recursive algorithms TRANSMISSION RATE

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Simultaneous Input and State Estimation with a Delay

Simultaneous Input and State Estimation with a Delay

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IEEE Annual Conference on Decision and Control

作者： Sze Zheng Yong Minghui Zhu Emilio Frazzoli Laboratory for Information and Decision Systems Massachusetts Institute of Technology Cambridge MA USA Department of Electrical Engineering Pennsylvania State University University Park PA USA

ISBN: (纸本)9781479978878

In this paper, we present recursive algorithms for linear discrete-time stochastic systems that simultaneously estimate the states and unknown inputs in an unbiased minimum-variance sense with a delay. By allowing potential delays in state estimation, the stricter assumptions in a previous work [1] can be relaxed. Moreover, we show that a system property known as strong detectability plays a key role in the existence and stability of the asymptotic estimator with a delay we propose.

关键词： State estimation delay recursive algorithms stochastic systems

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Reduction of latency and resource usage in bit-level pipelined data paths for FPGAs 99

Reduction of latency and resource usage in bit-level pipelin...

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Proceedings of the 1999 ACM/SIGDA seventh international symposium on Field programmable gate arrays

作者： P. Kollig B. M. Al-Hashimi School of Engineering and Advanced Technology Staffordshire University Beaconside Stafford ST18 OAD U.K.

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Incremental and Decremental Support Vector Machine Learning 00

Incremental and Decremental Support Vector Machine Learning

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Annual Conference on Neural Information Processing Systems

作者： Tomaso Poggio Gert Cauwenberghs CLSP ECE Dept. Johns Hopkins University Baltimore MD 21218

ISBN: (纸本)0262122413

An on-line recursive algorithm for training support vector machines, one vector at a time, is presented. Adiabatic increments retain the Kuhn-Tucker conditions on all previously seen training data, in a number of steps each computed analytically. The incremental procedure is reversible, and decremental "unlearning" offers an efficient method to exactly evaluate leave-one-out generalization performance. Interpretation of decremental unlearning in feature space sheds light on the relationship between generalization and geometry of the data.

关键词： Incremental Eigenvector Generalization Support Vector Network Training Support Steps geometry recursive algorithms Learning Training data Sheds

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A Piecewise and Bi-recursive Algorithm for Computing High-order Krawtchouk Moments

A Piecewise and Bi-recursive Algorithm for Computing High-or...

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International Conference on Computer Science and Network Technology

作者： Bo Li Yuqi Zhang School of Mechanical and Automotive Engineering Hubei University of Arts and Science Xiangyang 441053 China Automation Equipment Lab Collaborative Innovation Center of Hubei Province for Auto Parts Manufacturing Xiangyang 441053 China

ISBN: (纸本)9781467381741

A piecewise and bi-recursive algorithm for computing high-order Krawtchouk moments is proposed in this paper. The algorithm firstly puts forward a bi-recursive method to simplify the computation of Krawtchouk polynomials, and then the process of iteration is separated into several sections to limit iterative times of transmission error. Several experiments are carried out to examine the algorithm using grayscale image, and the results show that the algorithm has good performance in representation capability and recognition accuracy.

关键词： Krawtchouk moments piecewise bi-recursive high-order Piecewise higher-order grayscale images Transmission errors algorithms Moment of force recursive algorithms

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A Novel recursive Algorithm for Bit-Efficient Realization of Arbitrary Length Inverse Modified Cosine Transforms 08

A Novel Recursive Algorithm for Bit-Efficient Realization of...

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2008 Design, Automation and Test in Europe (DATE 2008), vol.2

作者： Ralf Koenig Timo Stripf Juergen Becker Universitaet Karlsruhe

ISBN: (纸本)9783981080131

In this paper a novel approach for Inverse Modified Cosine Transform (IMDCT) computation is presented, based on a recursive algorithm. Due to its nature, this IMDCT calculation can be performed on a reduced bit width datapath without loss of accuracy, compared to alternative recursive architectures. Combined with the regular structure, the approach allows for a much more area efficient VLSI implementation compared to existing systems. Due to its bit efficiency this approach is attractive to be implemented on reconfigurable architectures of the DSP domain as well.

关键词： recursive algorithms Reconfigurable architectures Cosine transforms Inverse Regular Binary digits discrete Fourier transform

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