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recursive computation method for fast encoding of vector quantization based on 2-pixel-merging sum pyramid data structure

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PATTERN RECOGNITION LETTERS 2005年第11期26卷 1684-1690页

作者： Pan, ZB Kotani, K Ohmi, T Tohoku Univ New Ind Creat Hatchery Ctr Aoba Ku Sendai Miyagi 9808579 Japan Tohoku Univ Grad Sch Engn Dept Elect Engn Aoba Ku Sendai Miyagi 9808579 Japan

Vector quantization (VQ) is a popular signal compression method. In the framework of VQ, fast search method is one of the key issues because it is the time bottleneck for VQ applications. in order to speed up VQ encoding process, how to construct some lower dimensional feature vectors for a k-dimensional original vector so as to measure the distortion between any vectors lightly becomes important. To reduce the dimension for approximately representing a k-dimensional vector, the multi-resolution concept is a natural consideration. By introducing a pyramid data structure, the multi-resolution concept used in fast VQ encoding includes two aspects, which are (1) a multi-resolution distortion check method and (2) a multi-resolution distortion computation method. Some fast search methods that are based on a 4-pixel-merging (4-PM) mean pyramid data structure [Lin, S.J., Chung, K.L., Chang, L.C. 2001. An improved search algorithm for vector quantization using mean pyramid structure. Pattern Recognition Lett. 22 (3/4) 373] and a 2-pixel-merging (2-PM) sum pyramid data structure [Pan, Z., Kotani, K., Ohmi, T. 2004. An improved fast encoding algorithm for vector quantization using 2-pixel-merging sum pyramid data structure. Pattern Recognition Lett. 25 (3) 459] have already been proposed. Both of them realized the multi-resolution concept by using a multi-resolution distortion check method. However, both of them ignored the multi-resolution distortion computation method, which can also be guaranteed by the multi-resolution concept if a recursive computation way is introduced. In principle, a multi-resolution distortion computation method can completely reuse the obtained computation result that is already executed at a lower resolution level so that Do waste to it will occur at all. This paper aims at improving the search efficiency of the previous work [Pan, Z., Kotani, K., Ohmi, T. 2004. An improved fast encoding algorithm for vector quantization using 2-pixel-merging sum p

关键词： recursive computation fast search vector quantization 2-pixel-merging sum pyramid

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recursive computation of Hermite spherical spline interpolants

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JOURNAL OF computationAL AND APPLIED MATHEMATICS 2008年第2期213卷 439-453页

作者： Lamnii, A. Mraoui, H. Sbibih, D. Univ Mohammed 1 Ecole Super Technol Lab MATSI Oujda Morocco

Let u be a function defined on a spherical triangulation Delta of the unit sphere S. In this paper, we study a recursive method for the construction of a Hermite spline interpolant u(k) of class l(k) and degree 4k + I on S, defined by some data scheme D-k(u). We show that when the data sets D-r(u) are nested, i.e., Dr-l (u) subset of D-r (u), l <=. r <=. k, the spline function u(k) can be decomposed as a sum of k + I simple elements. This decomposition leads to the construction of a new and interesting basis of a space of Hermite spherical splines. The theoretical results are illustrated by some numerical examples. (c) 2007 Elsevier B.V. All rights reserved.

关键词： spherical splines Hermite interpolation recursive computation decomposition

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recursive computation OF STEADY-STATE PROBABILITIES IN PRIORITY-QUEUES

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OPERATIONS RESEARCH LETTERS 1990年第4期9卷 249-256页

作者： CIDON, I SIDI, M TECHNION ISRAEL INST TECHNOL DEPT ELECT ENGNIL-32000 HAIFAISRAEL

Exact recursive formulas are derived for the state probabilities in priority queueing systems (preemptive and non-preemptive). The derivation is based only on the general structure of the generating function involved, and thus is simpler and more general than previous methods. Furthermore, applications of the method to other queueing systems are discussed.

关键词： priority queues recursive computation steady-state probabilities

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recursive computation of Steady State Probabilities in M/M/1/B Queues

Recursive Computation of Steady State Probabilities in M/M/1...

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International Conference on Electrical and Computing Technologies and Applications (ICECTA)

作者： Ahmed, Rana E. Amer Univ Sharjah Dept Comp Sci & Engn Sharjah U Arab Emirates

ISBN: (纸本)9781538608722

Several aspects related to the performance of wireless networks have been traditionally modeled with queueing theory. This paper presents a recursive procedure to find the steady state probabilities in an M/M/1/B queue from the steady state probabilities of an M/M/1/(B-1) queue. The procedure provides an alternative approach for the computation of state probabilities and provides better insight on how those probabilities change when the buffer size increases. A formula is developed for computing the relative decrease in the state probabilities when the buffer size is increased by one.

关键词： Analytical Models M/M/1 queue Finite Buffer Size recursive computation Steady State Probabilities

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recursive computation of the score and observed information matrix in Hidden Markov Models

Recursive computation of the score and observed information ...

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13th IEEE Workshop on Statistical Signal Processing

作者： Cappe, Olivier Moulines, Eric CNRS F-75634 Paris 13 France

ISBN: (纸本)0780394038

Hidden-Markov Models (henceforth abbreviated to HMMs), taken in their most general acception, that is including models in which the state space of the hidden chain is continuous have become a widely used class of statistical models with applications in diverse areas such as communications, engineering, bioinformatics. econometrics and many more. This contribution focus oil the computation of derivatives of the log-likelihood and proposes a (comparatively) simple and general framework. based oil the use of Fisher and Louis identities, to obtain recursive equations for computing the score and observed information matrix. This approach is thought to be simpler than (although equivalent to) the solution provided by the so-called sensitivity equations. It is based oil the original remark that recursive smoothers for HMMs are also available for some functionals of the hidden states which do not reduce to sum functionals. This view of the problem also suggests ways in which these exact equations could be approximated using sequential Monte Carlo methods.

关键词： Hidden Markov Models score information matrix smoothing recursive computation

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recursive computation OF CERTAIN DERIVATIVES - A STUDY OF ERROR PROPAGATION

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COMMUNICATIONS OF THE ACM 1970年第1期13卷 7-&页

作者： GAUTSCHI, W KLEIN, BJ Purdue Univ. Lafayette IN Virginia Polytechnic Institute Blacksburg

A brief study is made of the propagation of errors in linear first-order difference equations. The recursive computation of successive derivatives of θx/x and (cos x)/x is considered as an Illustration. [ABSTRACT FRO... 详细信息

关键词： error propagation recursive computation successive derivatives

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Improved recursive computation of clebsch-Gordan coefficients

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JOURNAL OF QUANTITATIVE SPECTROSCOPY & RADIATIVE TRANSFER 2020年 254卷 107210-107210页

作者： Xu, Guanglang Univ Helsinki Helsinki Finland

Fast, accurate, and stable computation of the Clebsch-Gordan (C-G) coefficients is always desirable, for example, in light scattering simulations, the translation of the multipole fields, quantum physics and chemistry. Current recursive methods for computing the C-G coefficients are often unstable for large quantum numbers due to numerical overflow or underflow. In this paper, we present an improved method, called the sign-exponent recurrence, for the recursive computation of C-G coefficients. The result shows that the proposed method can significantly improve the stability of the computation without losing its efficiency, producing accurate values for the C-G coefficients even with very large quantum numbers. (C) 2020 The Author. Published by Elsevier Ltd.

关键词： Clebsch-Gordan coefficients recursive computation Light scattering Translation coefficients Multipole fields T-Matrix

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S-TSP: A Novel Routing Algorithm for In-network Processing of recursive computation in Wireless Sensor Networks 4

S-TSP: A Novel Routing Algorithm for In-network Processing o...

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4th International Conference on Wireless and Optical Communications (IWOC)

作者： Tang, Tingfang Guo, Peng Liu, Xuefeng Huazhong Univ Sci & Technol Wuhan Peoples R China

ISBN: (纸本)9781510601550

In-network processing is an efficient way to reduce the transmission cost in wireless sensor networks (WSNs). The in-network processing of many domain-specific computation tasks in WSNs usually requires to losslessly distribute the computation of the tasks into the sensor nodes, which is however usually not easy. In this paper we are concerned with such kind of tasks whose computation can only be partitioned into recursive computation mode. To distribute the recursive computations into WSNs, it is required to design an appropriate single in-network processing path, along which the intermediate data is forwarded and updated in the WSNs. We address the recursive computation with constant size of computation result, e.g., distributed least square estimation (D-LSE). Finding the optimal in-network processing path to minimize the total transmission cost in WSNs, is a new problem and seldom studied before. To solve it, we propose a novel routing algorithm called as S-TSP, and compare it with some other greedy algorithms. Extensive simulations are conducted, and the results show the good performance of the proposed S-TSP algorithm.

关键词： wireless sensor networks in-network processing recursive computation routing algorithms

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An Online recursive computational Approach for the Closed-Loop Stability Margin of the PnP Process Monitoring and Control Structure 23

An Online Recursive Computational Approach for the Closed-Lo...

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23rd IEEE International Conference on Intelligent Engineering Systems (INES)

作者： Liu, Tianyu Luo, Hao Yin, Shen Kaynak, Okyay Harbin Inst Technol Dept Control Sci & Engn Harbin 150001 Peoples R China Bogazici Univ Mechatron Res & Applicat Ctr TR-34342 Istanbul Turkey

ISBN: (纸本)9781728112138

Aiming at the development of real-time control-performance-oriented fault diagnosis and fault-tolerant control, an online recursive computational approach is proposed in this paper for the closed-loop stability margin of the plug-and-play process monitoring and control architecture (PnP-PMCA). The core of the proposed approach is based on the recursive least square (RLS) technique, which avoids the online computation of the matrix inverse. With the proposed approach in this paper, real-time control-performance-oriented fault diagnosis can be achieved. The correctness and the effectiveness of the proposed approach are demonstrated through the case studies on a DC motor benchmark system.

关键词： Stability margin data-driven method recursive computation process monitoring

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Transparent Sequential Learning for Statistical Process Control of Serially Correlated Data

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TECHNOMETRICS 2022年第4期64卷 487-501页

作者： Qiu, Peihua Xie, Xiulin Univ Florida Dept Biostat 2004 Mowry Rd Gainesville FL 32610 USA

Machine learning methods have been widely used in different applications, including process control and monitoring. For handling statistical process control (SPC) problems, conventional supervised machine learning methods (e.g., artificial neural networks and support vector machines) would have some difficulties. For instance, a training dataset containing both in-control and out-of-control (OC) process observations is required by a supervised machine learning method, but it is rarely available in SPC applications. Furthermore, many machine learning methods work like black boxes. It is often difficult to interpret their learning mechanisms and the resulting decision rules in the context of an application. In the SPC literature, there have been some existing discussions on how to handle the lack of OC observations in the training data, using the one-class classification, artificial contrast, real-time contrast, and some other novel ideas. However, these approaches have their own limitations to handle SPC problems. In this article, we extend the self-starting process monitoring idea that has been employed widely in modern SPC research to a general learning framework for monitoring processes with serially correlated data. Under the new framework, process characteristics to learn are well specified in advance, and process learning is sequential in the sense that the learned process characteristics keep being updated during process monitoring. The learned process characteristics are then incorporated into a control chart for detecting process distributional shift based on all available data by the current observation time. Numerical studies show that process monitoring based on the new learning framework is more reliable and effective than some representative existing machine learning SPC approaches.

关键词： Data correlation Machine learning recursive computation Self-starting charts Sequential learning Statistical process control

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