• Title/Summary/Keyword: Downhill Simplex

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A Low Complicate Reverse Rake Beamforming Algorithm Based On Simplex Downhill Optimization Method For DS/CDMA Communication (Simplex Downhill 최적화 기법을 기반으로 하는 간략화 된 DS/CDMA 역방향 링크 Rake Beamforming Method)

  • Lee Sang-Keun;Lee Yoon-Hyun
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.31 no.3A
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    • pp.249-253
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    • 2006
  • We propose a new beamforming algorithm, which is based on simplex downhill optimization method in the presence of pilot channels in cdma2000 reverse-link, for the rake structure antenna array in DS/CDMA communication system. Our approach uses the desired signal(pilot) covariance matrix and the interference covariance matrix. The beamforming weights are made according to maximum SINR criteria using simplex downhill optimization procedure. Our proposed scheme provides lower computational load, better convergence speed, better performance than existingadaptive beamforming algorithm. The simplex downhill method is well suited to finding the optimal or sub-optimal weight vector, since they require only the value of the deterministic function to be optimized. The rake beamformer performances are also evaluated under several set of practical parameter values with regard to spatial channel model. We also compare the performance between conventional rake receiver and the proposed one under same receiving power.

State Machine and Downhill Simplex Approach for Vision-Based Nighttime Vehicle Detection

  • Choi, Kyoung-Ho;Kim, Do-Hyun;Kim, Kwang-Sup;Kwon, Jang-Woo;Lee, Sang-Il;Chen, Ken;Park, Jong-Hyun
    • ETRI Journal
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    • v.36 no.3
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    • pp.439-449
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    • 2014
  • In this paper, a novel vision-based nighttime vehicle detection approach is presented, combining state machines and downhill simplex optimization. In the proposed approach, vehicle detection is modeled as a sequential state transition problem; that is, vehicle arrival, moving, and departure at a chosen detection area. More specifically, the number of bright pixels and their differences, in a chosen area of interest, are calculated and fed into the proposed state machine to detect vehicles. After a vehicle is detected, the location of the headlights is determined using the downhill simplex method. In the proposed optimization process, various headlights were evaluated for possible headlight positions on the detected vehicles; allowing for an optimal headlight position to be located. Simulation results were provided to show the robustness of the proposed approach for nighttime vehicle and headlight detection.

Parameter Calibrations of a Daily Rainfall-Runoff Model Using Global Optimization Methods (전역최적화 기법을 이용한 강우-유출모형의 매개변수 자동보정)

  • Kang, Min-Goo;Park, Seung-Woo;Im, Sang-Jun;Kim, Hyun-Jun
    • Journal of Korea Water Resources Association
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    • v.35 no.5
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    • pp.541-552
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    • 2002
  • Two global optimization methods, the SCE-UA method and the Annealing-Simplex(A-S) method for calibrating a daily rainfall-runoff model, a Tank model, was compared with that of the Downhill Simplex method. In synthetic data study, 100% success rates for all objective functions were obtained from the A-S method, and the SCE-UA method was also consistently able to obtain good estimates. The Downhill Simplex method was converged to the true values only when the initial guess was close to the true values. In the historical data study, the A-S method and the SCE-UA method showed consistently good results regardless of objective function. An objective function was developed, which puts more weight on the low flows.

Comparison of Automatic Calibration for a Tank Model with Optimization Methods and Objective Functions

  • Kang, Min-Goo;Park, Seung-Woo;Park, Chang-Eun
    • Magazine of the Korean Society of Agricultural Engineers
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    • v.44 no.7
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    • pp.1-13
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    • 2002
  • Two global optimization methods, the SCE-UA method and the Annealing-simplex (A-S) method for calibrating a daily rainfall-runoff model, a Tank model, was compared with that of the Downhill Simplex method. The performance of the four objective functions, DRMS (daily root mean square), HMLE (heteroscedastic maximum likelihood estimator), ABSERR (mean absolute error), and NS (Nash-Sutcliffe measure), was tested and synthetic data and historical data were used. In synthetic data study. 100% success rates for all objective functions were obtained from the A-S method, and the SCE-UA method was also consistently able to obtain good estimates. The downhill simplex method was unable to escape from local optimum, the worst among the methods, and converged to the true values only when the initial guess was close to the true values. In the historical data study, the A-S method and the SCE-UA method showed consistently good results regardless of objective function. An objective function was developed with combination of DRMS and NS, which putted more weight on the low flows.

Motion-Vector Refinement for Video Error Concealment Using Downhill Simplex Approach

  • Kim, Do-Hyun;Kwon, Young-Jin;Choi, Kyoung-Ho
    • ETRI Journal
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    • v.40 no.2
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    • pp.266-274
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    • 2018
  • In error-prone wireless environments, it is difficult to realize video coding systems that are robust to various types of data loss. In this paper, a novel motion-vector refinement approach is presented for video error concealment. A traditional boundary-matching approach is exploited to reduce blocky effects along the block boundary. More specifically, a downhill simplex approach is combined with a boundary-matching approach to fine-tune the motion vectors, reducing the blocky effects along the prediction unit block boundary, and minimizing the computational cost. Extensive simulations are performed, and the results obtained verify the robustness and effectiveness of the proposed approach.

Computation of 3D Coordinates from Stereo Images with RPCs (RPC를 이용한 Stereo 영상으로부터의 3차원 좌표 추출)

  • Kim Kwang-Eun
    • Korean Journal of Remote Sensing
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    • v.21 no.2
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    • pp.135-143
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    • 2005
  • RPC(Rational Polynomial Camera) models have become the replacement model of choice for a number of high resolution satellite imagery providers. RPCs(Rational Polynomial Coefficients) provide a compact accurate representation of the ground to image geometry, allowing users to perform full photogrammetric processing of satellite imagery including block adjustment, 3D feature extraction and orthorectification. This paper presents an algorithm for 3D feature extraction using downhill simpler method which requires only function evaluations, not derivatives. The algorithm was implemented as an executable software program and tested using stereo IKONOS images of Seoul city. The results showed that the proposed algorithm was fast and accurate enough to be used as a practical method for the 3D feature extraction from stereo images with RPCs.

Enhanced Antibiotic Production by Streptomyces sindenensis Using Artificial Neural Networks Coupled with Genetic Algorithm and Nelder-Mead Downhill Simplex

  • Tripathi, C.K.M.;Khan, Mahvish;Praveen, Vandana;Khan, Saif;Srivastava, Akanksha
    • Journal of Microbiology and Biotechnology
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    • v.22 no.7
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    • pp.939-946
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    • 2012
  • Antibiotic production with Streptomyces sindenensis MTCC 8122 was optimized under submerged fermentation conditions by artificial neural network (ANN) coupled with genetic algorithm (GA) and Nelder-Mead downhill simplex (NMDS). Feed forward back-propagation ANN was trained to establish the mathematical relationship among the medium components and length of incubation period for achieving maximum antibiotic yield. The optimization strategy involved growing the culture with varying concentrations of various medium components for different incubation periods. Under non-optimized condition, antibiotic production was found to be $95{\mu}g/ml$, which nearly doubled ($176{\mu}g/ml$) with the ANN-GA optimization. ANN-NMDS optimization was found to be more efficacious, and maximum antibiotic production ($197{\mu}g/ml$) was obtained by cultivating the cells with (g/l) fructose 2.7602, $MgSO_4$ 1.2369, $(NH_4)_2PO_4$ 0.2742, DL-threonine 3.069%, and soyabean meal 1.952%, for 9.8531 days of incubation, which was roughly 12% higher than the yield obtained by ANN coupled with GA under the same conditions.

Magnetoencephalography Source Localization using Improved Downhill Simplex Method in Frequency Domain (개선된 다운힐 심플렉스 법을 이용한 주파수 영역에서의 뇌자도 신호원 추정)

  • Kim, Byeong-Jun;An, Kwang-Ok;Lee, Chany;Jung, Hyun-Kyo
    • Journal of Biomedical Engineering Research
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    • v.29 no.3
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    • pp.231-238
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    • 2008
  • Nelder-Mead downhill simplex method (DSM), a kind of deterministic optimization algorithms, has been used extensively for magnetoencephalography(MEG) dipolar source localization problems because it dose not require any functional differentiation. Like many other deterministic algorithms, however, it is very sensitive to the choice of initial positions and it can be easily trapped in local optima when being applied to complex inverse problems with multiple simultaneous sources. In this paper, some modifications have been made to make up for DSM's limitations and improve the accuracy of DSM. First of all, initial point determination method for DSM using magnetic fields on the sensor surface was proposed. Secondly, Univariant-DSM combined DSM with univariant method was proposed. To verify the performance of the proposed method, it was applied to simulated MEG data and practical MEG measurements.

Vignetting Dimensional Geometric Models and a Downhill Simplex Search

  • Kim, Hyung Tae;Lee, Duk Yeon;Choi, Dongwoon;Kang, Jaehyeon;Lee, Dong-Wook
    • Current Optics and Photonics
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    • v.6 no.2
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    • pp.161-170
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    • 2022
  • Three-dimensional (3D) geometric models are introduced to correct vignetting, and a downhill simplex search is applied to determine the coefficients of a 3D model used in digital microscopy. Vignetting is nonuniform illuminance with a geometric regularity on a two-dimensional (2D) image plane, which allows the illuminance distribution to be estimated using 3D models. The 3D models are defined using generalized polynomials and arbitrary coefficients. Because the 3D models are nonlinear, their coefficients are determined using a simplex search. The cost function of the simplex search is defined to minimize the error between the 3D model and the reference image of a standard white board. The conventional and proposed methods for correcting the vignetting are used in experiments on four inspection systems based on machine vision and microscopy. The methods are investigated using various performance indices, including the coefficient of determination, the mean absolute error, and the uniformity after correction. The proposed method is intuitive and shows performance similar to the conventional approach, using a smaller number of coefficients.

Performance Evaluation of Barlat's and BBC Yield Criteria based on Directionalities of R-values and Yield Stresses

  • Lou, Y.;Bae, G.;Lee, C.;Park, C.;Buh, H.
    • Proceedings of the Korean Society for Technology of Plasticity Conference
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    • 2009.10a
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    • pp.277-280
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    • 2009
  • This paper deals with the performance evaluation of Barlat's and BBC yield criteria by the directional variation prediction of the yield stresses and the R-values. for the evaluation of yield criteria, three kinds of Aluminum alloys and two kinds of steels were selected and their material properties are from Stoughton and Yoon's work. The experimental data required for the parameter evaluation included the uniaxial yield stresses and R-values (width-to-thickness strain ratio in uniaxial tension) measured in rolling direction, diaganol direction and the transverse direction, the equibiaxial yield stress and the R-value of equibiaxial tension. The optimization method, the Downhill Simplex method, was selected for the coefficient identification of Barlat91, Barlat97 and Barlat2000 yield criteria. Yield surface shapes, yield stress and R-value directionalities of Barlat's and BBC yield criteria were investigated and compared with the experimental data. Barlat2000 and BBC yield criteria were extremely qualified for the shape of the yield surface and the directionality of the yield stresses and the R-values.

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