• Title/Summary/Keyword: Gradient Vector Calculation

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Effect of Gradient Vector Calculation Method On Adaptive Beamforming using LMS Algorithm (기울기 벡터 계산법이 LMS 알고리즘을 이용한 적응 빔포밍에 미치는 영향)

  • Kwang-Chol Chae;Ki-Ryang Cho
    • The Journal of the Korea institute of electronic communication sciences
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    • v.18 no.3
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    • pp.535-544
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    • 2023
  • In this paper, we study the effect of gradient vector calculation method(analytical method, central finite difference method) on adaptive beamforming to control weight distribution during iterated calculation when LMS algorithm (repeating method) is used to realize desired beam pattern. To this end, a quasi-ideal beam having an arbitrarily set beam width, a rotating beam, and a multi-beam were reviewed as examples. Numerical experiments applied the step parameters of the appropriate values to the adaptive beamforming system through trial and error equally to the two calculations, and compared the convergence characteristics of objective functions that evaluate adaptability and error using two methods for calculating gradient vectors.

High-Performance and Low-Complexity Image Pre-Processing Method Based on Gradient-Vector Characteristics and Hardware-Block Sharing

  • Kim, Woo Suk;Lee, Juseong;An, Ho-Myoung;Kim, Jooyeon
    • Transactions on Electrical and Electronic Materials
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    • v.18 no.6
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    • pp.320-322
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    • 2017
  • In this paper, a high-performance, low-area gradient-magnitude calculator architecture is proposed, based on approximate image processing. To reduce the computational complexity of the gradient-magnitude calculation, vector properties, the symmetry axis, and common terms were applied in a hardware-resource-shared architec-ture. The proposed gradient-magnitude calculator was implemented using an Altera Cyclone IV FPGA (EP4CE115F29) and the Quartus II v.16 device software. It satisfied the output-data quality while reducing the logic elements by 23% and the embedded multipliers by 76%, compared with previous work.

Iris Recognition Using Vector Summation Of Gradient Orientation Vectors (그래디언트 방향 벡터의 벡터합을 이용한 홍채 인식)

  • Choi, Chang-Soo;Yoo, Kwan-Hee;Jun, Byoung-Min
    • The Journal of the Korea Contents Association
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    • v.9 no.8
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    • pp.121-128
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    • 2009
  • Iris recognition is a biometric technology which can identify a person using the iris pattern. Recently, iris information is used in many fields such as access control and information security. It is important for the iris recognition system to extract the feature which is invariant to changes in iris patterns. Those changes can be occurred by the influence of lights, changes in the size of the pupil. In this paper, we propose a novel method based on vector summation of gradient orientation vectors. Experimental results show that the proposed method reduces processing time with simple vector calculation, requires small feature space and has comparable performance to the well-known previous methods.

The Parameter Auto-tuning of the Reference Model Following Fuzzy Logic Controller (기준모델 추종 퍼지 제어기의 파라메터 자동 동조)

  • Roh, Chung-Min;Suh, Seung-Hyun;Ko, Bong-Woon;Nam, Moon-Hyon
    • Proceedings of the KIEE Conference
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    • 1996.07b
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    • pp.1377-1379
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    • 1996
  • In this paper, each parameter was identified by the gradient descent method to overcome difficulty deciding fuzzy rules of FLC for the unknown process and the type of membership Junctions. Usually PID or optimal control theories have been mostly usee in control field so far. However, optimal control requires much time for calculation because of adaptation for disturbance and nonlinearity. And intricate technique such as MRAS which can be realized only by an expert are limited to be used in the systems requiring rapid and precise response because of comparatively longer calculating time and complicateness. Gradient descent method is a method to find Z minimizing a function about a certain vector Z. And required output of FLC is gained using gradient approaching method in order to adapt control rule parameters of FLC. Simulation proved validation of this algorithm.

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An time-varying acoustic channel estimation using least squares algorithm with an average gradient vector based a self-adjusted step size and variable forgetting factor (기울기 평균 벡터를 사용한 가변 스텝 최소 자승 알고리즘과 시변 망각 인자를 사용한 시변 음향 채널 추정)

  • Lim, Jun-Seok
    • The Journal of the Acoustical Society of Korea
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    • v.38 no.3
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    • pp.283-289
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    • 2019
  • RLS (Recursive-least-squares) algorithm is known to have good convergence and excellent error level after convergence. However, there is a disadvantage that numerical instability is included in the algorithm due to inverse matrix calculation. In this paper, we propose an algorithm with no matrix inversion to avoid the instability aforementioned. The proposed algorithm still keeps the same convergence performance. In the proposed algorithm, we adopt an averaged gradient-based step size as a self-adjusted step size. In addition, a variable forgetting factor is introduced to provide superior performance for time-varying channel estimation. Through simulations, we compare performance with conventional RLS and show its equivalency. It also shows the merit of the variable forgetting factor in time-varying channels.

Development of Line Density Index for the Quantification of Oceanic Thermal Fronts (해양의 수온전선 정량화를 위한 선밀도 지수 개발)

  • Cho, Hyun-Woo;Kim, Kye-Hyun
    • Journal of the Korean Association of Geographic Information Studies
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    • v.9 no.2
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    • pp.227-238
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    • 2006
  • Line density index(LDI) was developed to quantify a densely isothermal line rate as standard index in the ocean environment. Theoretical background on the LDI development process restricting index range 0 to 100 was described. And validation test was done for the LDI application condition that total line length is not greater than 1/10 of unit area. NOAA SST(Sea Surface Temperature) data were used for the experimental application of LDI in the South Sea of Korea. Using GIS, $0.1^{\circ}C$ isothermal lines were linearized as vector data form SST raster data, and unit area were built as polygon data. For the LDI calculation, spatial overlapping(line in polygon) was implemented. To analyze the effect of unit area size for the LDI distribution, two cases of unit area size were designed and descriptive statistics was calculated including performing normality test. The results showed no change of LDI's essential characteristics such as mean and normality except for the range of value, variance and standard deviation. Accordingly, it was found that complex structure of thermal front and even smaller scale of front width than unit area size could influence on the LDI distribution. Also, correlation analysis performed between LDI and difference of temperature(${\Delta}T^{\circ}C$), and horizontal thermal gradient(${\Delta}T^{\circ}C/km$) on the front was obtained from linear regression model. This obtained value was compared with the results from previous researches. Newly developed LDI can be used to compare the thermal front regions changing spatio-temporally in the ocean environment using absolute index value. It is considered to be significant to analyze the relationship between thermal front and marine environment or front and marine organisms in a quantitative approach described in this study.

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