• Wind and Structures
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• v.4 no.2
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• pp.101-118
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• 2001

This paper reports the field measurements concerning pressure equalization of rainscreen facades carried out at the Technical University of Eindhoven (TUE) in the Netherlands. The field facility including the details of test panel, meteorological tower, instrumentation, data collection and analysis is presented. Results of investigations into cavity response for various leakage and venting configurations are discussed. Frequency domain techniques have been utilized to show the influence of wind as well as facade characteristics on the pressure equalization performance. Further, this paper presents an early attempt to synthesize the experimental results into existing building codes.

• Proceedings of the IEEK Conference
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• 1999.11a
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• pp.47-50
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• 1999

Adaptive channel equalization accomplished without resorting to a training sequence is known as blind equalization. The Constant Modulus Algorithm(CMA) and Modified CMA(MCMA) are widely referenced algorithms for blind equalization of a QAM system. This paper proposes a hybrid scheme of CMA and MCMA with Carrier Recovery that is robust for high level QAM with low steady state tracking error.

• The Journal of the Acoustical Society of Korea
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• v.26 no.2E
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• pp.63-68
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• 2007

Using the neural network model for oriented principal component analysis (OPCA), we propose a solution to the data least squares (DLS) problem, in which the error is assumed to lie in the data matrix only. In this paper, we applied this neural network model to channel equalization. Simulations show that the neural network based DLS outperforms ordinary least squares in channel equalization problems.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.46 no.1
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• pp.10-21
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• 2009

In order to enhance the contrast in the regions where the pixels have similar intensities, this paper presents a new histogram equalization scheme. Conventional global equalization schemes over-equalizes those regions so that too bright or dark pixels are resulted and local equalization schemes produce unexpected discontinuities at the boundaries of the blocks. The proposed algorithm segments the original histogram into sub-histograms with reference to brightness level and equalizes each sub-histogram with the limited extents of equalization considering its mean and variance. The final image is determined as the weighted sum of the equalized images obtained by using the sub-histogram equalizations. By limiting the maximum and minimum ranges of equalization operations on individual sub-histograms, the over-equalization effect is eliminated. Also the result image does not miss feature information in low density histogram region since the remaining these area is applied separating equalization. This paper includes how to determine the segmentation points in the histogram. The proposed algorithm has been tested with more than 100 images having various contrast in the images and the results are compared to the conventional approaches to show its superiority.

• The Journal of the Acoustical Society of Korea
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• v.33 no.1
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• pp.68-74
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• 2014

In a previous work, we proposed a novel approach of histogram equalization using a supplement set which is composed of centroids of Fuzzy C-Means of the background utterances. The performance of the proposed method is affected by the size of the supplement set, but it is difficult to find the best size at the point of recognition. In this paper, we propose a histogram equalization using a supplement set for majority voting based speaker identification. The proposed method identifies test utterances using a majority voting on the histogram equalization methods with various sizes of supplement sets. The proposed method is compared with the conventional feature normalization methods such as CMN(Cepstral Mean Normalization), MVN(Mean and Variance Normalization), and HEQ(Histogram Equalization) and the histogram equalization method using a supplement set.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.23 no.11
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• pp.1377-1383
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• 2019

Histogram equalization is the most frequently used algorithm for image enhancement. Its hardware implementation significantly outperforms in time its software version. The overall performance of FPGA-based implementation of histogram equalization can be improved by applying pipelining in the design and by exploiting the multipliers and a lot of SRAM blocks which are embedded in recent FPGAs. This work proposes how to implement a fast histogram equalization circuit for 8-bit gray level images. The proposed design contains a FIFO to perform equalization on an image while the histogram for next image is being calculated. Because of some overlap in time for histogram equalization, embedded multipliers and pipelined design, the proposed design can perform histogram equalization on a pixel nearly at a clock. And its dual parallel version outperforms in time almost two times over the original one.

• ETRI Journal
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• v.18 no.2
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• pp.53-60
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• 1996

Blind equalization is a technique for adaptive equalization of a communication channel without the aid of training sequences. This paper proposes a new blind equalization algorithm. The advantage of the new algorithm is that it has the lower residual error than the GA (proposed by Godard) and Sign_GA (proposed by Weerackody et al.). The superior performance of the proposed algorithm is illustrated for the 16-QAM signal constellation. A Rummler channel model is assumed as a transmission medium. The performance of the proposed algorithm is compared to the GA, Sign_GA and Stop & Go Algorithm (SGA). The simulation results demonstrate that an improvement in performance is achieved with the proposed equalization algorithm.

• Wind and Structures
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• v.2 no.4
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• pp.325-345
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• 1999

In recent years, rainscreen walls based on the pressure equalization principle are often used in building construction. To improve the understanding of the influence of several design parameters on the pressure equalization performance of such wall systems, a theoretical consideration of the problem may be more appropriate. On this basis, this paper presents two theoretical models, one based on mass balance and the other based on the Helmholtz resonator theory, for the prediction of cavity pressure in rigid rainscreen walls. New measures to assess the degree of pressure equalization of rainscreen walls are also suggested. The results show that the model based on mass balance is sufficiently accurate and efficient in predicting the cavity pressure variations. Further, the performance of the proposed model is evaluated utilizing the data obtained from full-scale tests and the results are discussed in detail.

• Journal of Korea Multimedia Society
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• v.18 no.6
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• pp.691-700
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• 2015

Here, we present a new framework for histogram equalization in which both local and global contrasts are enhanced using neighborhood metrics. When checking neighborhood information, filters can simultaneously improve image quality. Filters are chosen depending on image properties, such as noise removal and smoothing. Our experimental results confirmed that this does not increase the computational cost because the filtering process is done by our proposed arrangement of making the histogram while checking neighborhood metrics simultaneously. If the two methods, i.e., histogram equalization and filtering, are performed sequentially, the first method uses the original image data and next method uses the data altered by the first. With combined histogram equalization and filtering, the original data can be used for both methods. The proposed method is fully automated and any spatial neighborhood filter type and size can be used. Our experiments confirmed that the proposed method is more effective than other similar techniques reported previously.

• Journal of the Korean Society of Industry Convergence
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• v.13 no.1
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• pp.23-30
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• 2010

This paper presents a histogram equalization based on the nonlinear transformation function for enhancing the quality of medical images. The nonlinear transformation function is applied to adaptively equalize the brightness of the image according to its intensity level frequency. The logistic function is used as a nonlinear transformation function, which is calculated by only using the intensity level with maximum frequency and the maximum intensity level in an histogram, and the total number of pixels. The proposed method has been applied for equalizing 8 medical images with a different resolution and histogram distribution. The experimental results show that the proposed method has the superior enhancement performances compared with the conventional histogram equalization. And the proposed histogram equalization can be used in various multimedia systems in real-time.