• Title/Summary/Keyword: Weighting algorithm

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Nonlinear structural system wind load input estimation using the extended inverse method

  • Lee, Ming-Hui
    • Wind and Structures
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    • v.17 no.4
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    • pp.451-464
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    • 2013
  • This study develops an extended inverse input estimation algorithm with intelligent adaptive fuzzy weighting to effectively estimate the unknown input wind load of nonlinear structural systems. This algorithm combines the extended Kalman filter and recursive least squares estimator with intelligent adaptive fuzzy weighting. This study investigated the unknown input wind load applied on a tower structural system. Nonlinear characteristics will exist in various structural systems. The nonlinear characteristics are particularly more obvious when applying larger input wind load. Numerical simulation cases involving different input wind load types are studied in this paper. The simulation results verify the nonlinear characteristics of the structural system. This algorithm is effective in estimating unknown input wind loads.

Vertical Handoff Decision Algorithm combined Improved Entropy Weighting with GRA for Heterogeneous Wireless Networks

  • Zhao, Shasha;Wang, Fei;Ning, Yueqiang;Xiao, Yi;Zhang, Dengying
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.14 no.11
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    • pp.4611-4624
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    • 2020
  • Future network scenario will be a heterogeneous wireless network environment composed of multiple networks and multimode terminals (MMT). Seamless switching and optimal connectivity for MMT among different networks and different services become extremely important. Here, a vertical handoff algorithm combined an improved entropy weighting method based on grey relational analysis (GRA) is proposed. In which, the improved entropy weight method is used to obtain the objective weights of the network attributes, and GRA is done to rank the candidate networks in order to choose the best network. Through simulation and comparing the results with other vertical handoff decision algorithms, the number of handoffs and reversal phenomenon are reduced with the proposed algorithm, which shows a better performance.

An algorithm for pahse detection using weighting function and the design of a phase tracking loop (가중치 함수를 이용한 위상 검출 알고리즘과 위상 추적 루프의 설계)

  • 이명환
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.23 no.9A
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    • pp.2197-2210
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    • 1998
  • In the grand alliance (GA) HDTV receiver, a coherent detection is empolyed for coherent demodulation of vestigial side-band (VSB) signal by using frequency and phaselocked loop(FPLL) operating on the pilot carrier. Additional phase tracking loop (PTL) employed to track out phase noise that has not been removed by the FPLL in theGA system. In this paper, we propose an algorithm for phase detection which utilizes a weighting function. The simplest implementation of the proposed algorithm using te sign of the Q channel component can be tractable by imposing a phase detection gain to the loop gain. It is obserbed that the propsoed algorithm has a robust characteristic against the performance of the digital filters used for Q channel estimation. A second goal of this paper is to introduce a gain control algorithm for the PTL in order to provide an effective implementation of the proposed phase detection algorithm. And we design the PTL through the realization of the simplified digital filter for H/W reduction. The proposed algorithms and the designed PTL are evaluated by computer simulation. In spite of using the simplified H/W structure, simulation results show that the proposed algorithms outperform the coventional PTL algorithms in the phase detection and tracking performance.

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An Algorithm on Optimum Weighting Design in Beamforming for Acoustic Measurement (음향측정을 위한 빔형성에서의 최적 가중상수 설계 기법)

  • Dho, Kyeong-Cheol;Son, Kweon;Lee, Yong-Gon;Son, Kyung-Sik
    • The Journal of the Acoustical Society of Korea
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    • v.18 no.8
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    • pp.61-67
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    • 1999
  • This paper proposes a new beamforming algorithm for acoustic measurement by using the nested linear array. In this algorithm, the weighting is optimized by minimizing the LMS error with the initial value obtained by FIR filter design algorithm. The optimization process is applied to each sub-band, which is divided from the octave band, to produce the uniform directivity index. For the optimization pseudo inverse matrix is used for the transfer matrix. As the simulation results, it is found that the proposed algorithm can get the desired beam pattern and unform directivity index so as to be used efficiently for the acoustic measurement by using a nested linear array.

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A Design on Model-Following $H_{\infty}$ Control System Having Robust Performance (강인한 성능을 가지는 모델추종형 $H_{\infty}$ 제어 시스템의 설계)

  • Hwang, Hyun-Joon
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.13 no.5
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    • pp.913-921
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    • 2009
  • This paper suggests a deign method of the model-following $H{\infty}$ control system having robust performance. This $H{\infty}$ control system is designed by applying genetic algorithm(GA) with reference model to the optimal determination of weighting functions and design parameter ${\gamma}$ that are given by $H{\infty}$ control theory. These weighting functions and design parameter ${\gamma}$ are optimized simultaneously in the search domain guaranteeing the robust performance of closed-loop system. The effectiveness of this $H_{\infty}$ control system is verified by computer simulation.

A Design Weighting Polynomial Parameter Tuning of a Self Tuning Controller (자기동조 제어기의 설계 하중다항식 계수 조정)

  • 조원철;김병문
    • Journal of the Korean Institute of Telematics and Electronics T
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    • v.35T no.3
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    • pp.87-95
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    • 1998
  • This paper presents the method for the automatic tuning of a design weighting polynomial parameter of a generalized minimum-variance stochastic self tuning controller which adapts to changes in the system parameters with time delays and noises. The self tuning effect is achieved through the recursive least square algorithm at the parameter estimation stage and also through the Robbins-Monro algorithm at the stage of optimizing a design weighting polynomial parameters. The proposed self tuning method is simple and effective compared with other existing self tuning methods. The computer simulation results are presented to illustrate the procedure and to show the performance of the control system.

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Multi-criteria Vertical Handoff Decision Algorithm Using Hierarchy Modeling and Additive Weighting in an Integrated WLAN/WiMAX/UMTS Environment- A Case Study

  • Bhosale, Sahana;Daruwala, Rohin
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.8 no.1
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    • pp.35-57
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    • 2014
  • Multi-criteria decision making (MCDM) algorithms play an important role in ensuring quality of service in an integrated HetNets (Heterogeneous Networks). The primary objective of this paper is to develop a multi-criteria vertical handoff decision algorithm (VHDA) for best access network selection in an integrated Wireless Local Area Network (WLAN)/Universal Mobile Telecommunications System (UMTS)/Worldwide Interoperability for Microwave Access (WiMAX) system. The proposed design consists of two parts, the first part is the evaluation of an Analytic Hierarchy Process (AHP) to decide the relative weights of handoff decision criteria and the second part computes the final score of the weights to rank network alternatives using Simple Additive Weighting (SAW). SAW ranks the network alternatives in a faster and simpler manner than AHP. The AHP-SAW mathematical model has been designed, evaluated and simulated for streaming video type of traffic. For other traffic type, such as conversational, background and interactive, only simulation results have been discussed and presented in brief. Simulation results reveal that the hierarchical modelling and computing provides optimum solution for access network selection in an integrated environment as obtained results prove to be an acceptable solution to what could be expected in real life scenarios.

Speech Verification using Similar Word Information in Isolated Word Recognition (고립단어 인식에 유사단어 정보를 이용한 단어의 검증)

  • 백창흠;이기정홍재근
    • Proceedings of the IEEK Conference
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    • 1998.10a
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    • pp.1255-1258
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    • 1998
  • Hidden Markov Model (HMM) is the most widely used method in speech recognition. In general, HMM parameters are trained to have maximum likelihood (ML) for training data. This method doesn't take account of discrimination to other words. To complement this problem, this paper proposes a word verification method by re-recognition of the recognized word and its similar word using the discriminative function between two words. The similar word is selected by calculating the probability of other words to each HMM. The recognizer haveing discrimination to each word is realized using the weighting to each state and the weighting is calculated by genetic algorithm.

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Direct Model Reference Adaptive Pole Pacement Control with Exponential Weighting Properties (지수함수적 가중특성의 기준 모델 직접 적응 극배치 제어)

  • Kim, Jong-Hwan;Kwack, Jeong-Hun
    • Proceedings of the KIEE Conference
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    • 1990.07a
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    • pp.51-54
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    • 1990
  • A parametrization for a linear system is presented to design a direct model reference adaptive pole placement controler. This parametrized model is one of the structured nonminimal models. The exponentially weighted least-squres algorithm is employed to estimate the control parameters. The direct adaptive controller has the exponential weighting properties by the proposed method of selecting the characteristic polynomials of the sensitivity function filters in connection with the reference models.

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Evaluation of Optimum Genetic Contribution Theory to Control Inbreeding While Maximizing Genetic Response

  • Oh, S.H.
    • Asian-Australasian Journal of Animal Sciences
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    • v.25 no.3
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    • pp.299-303
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    • 2012
  • Inbreeding is the mating of relatives that produce progeny having more homozygous alleles than non-inbred animals. Inbreeding increases numbers of recessive alleles, which is often associated with decreased performance known as inbreeding depression. The magnitude of inbreeding depression depends on the level of inbreeding in the animal. Level of inbreeding is expressed by the inbreeding coefficient. One breeding goal in livestock is uniform productivity while maintaining acceptable inbreeding levels, especially keeping inbreeding less than 20%. However, in closed herds without the introduction of new genetic sources high levels of inbreeding over time are unavoidable. One method that increases selection response and minimizes inbreeding is selection of individuals by weighting estimated breeding values with average relationships among individuals. Optimum genetic contribution theory (OGC) uses relationships among individuals as weighting factors. The algorithm is as follows: i) Identify the individual having the best EBV; ii) Calculate average relationships ($\bar{r_j}$) between selected and candidates; iii) Select the individual having the best EBV adjusted for average relationships using the weighting factor k, $EBV^*=EBV_j(1-k\bar{{r}_j})$ Repeat process until the number of individuals selected equals number required. The objective of this study was to compare simulated results based on OGC selection under different conditions over 30 generations. Individuals (n = 110) were generated for the base population with pseudo random numbers of N~ (0, 3), ten were assumed male, and the remainder female. Each male was mated to ten females, and every female was assumed to have 5 progeny resulting in 500 individuals in the following generation. Results showed the OGC algorithm effectively controlled inbreeding and maintained consistent increases in selection response. Difference in breeding values between selection with OGC algorithm and by EBV only was 8%, however, rate of inbreeding was controlled by 47% after 20 generation. These results indicate that the OGC algorithm can be used effectively in long-term selection programs.