• The Journal of Korean Institute of Communications and Information Sciences
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• v.17 no.4
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• pp.387-397
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• 1992

The spatial domain design of 2-dimensional separable denominator digital filters(SDDF) based on the reduced dimensional decomposition can be realized when the given 2-D impulse response specifications are decomposed into a pair of 1-D specifications via singular value decompositions(SVD). Because of use of the balaned approximation and equivalent transform as 1-D design algorithm, 2-D design algorithm retains the advantage that is numerically stable and can minimize quantization errors. In this paper in order to analyze and reduce these errors, minimum comfficient quantization realization is directly derived from impulse response specification. And using the equivalent trans form relation between mininum coefficient quantization error and minimum roundoff error realizations, we optimally realize a SDDF. This algorithm is analyzed by the simulation, which shows that it is superior to direct or balanced realization in quantization errors.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.5 no.7
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• pp.1346-1353
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• 2001

This paper presents an algorithm for the design of 2 dimension separable denominator digital filter(SDDF). The proposed algorithm is based on the reduced dimensional decomposition not only 2 dimension SDDF's but also of given 2 dimension specification. The frequency domain design of 2 dimension separable denominator digital filters based on the reduced dimensional decomposition can be realized when the given 2 dimension frequency specification are optimally decomposed into a pair of 1 dimension digital filter specification via singular value decomposition. the algorithm is computationally efficient and numerically stable. In case of the low pass filter, the approximation error of the proposed design algorithm is $e_{m}$=5.17, $e_{r1}$ =8.78, $e_{r2}$=7.34, while in case of band pass filter, the approximation error is $e_{m}$=13.00, $e_{r1}$=62.76, $e_{r2}$=62.7676.7676

• Journal of the Korean Mathematical Society
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• v.34 no.2
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• pp.279-284
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• 1997

Let L/F be a finite separable extension of Henselian valued fields with same residue fields $\overline{L} = \overline{F}$. Let D be an inertially split division algebra over L, and let $^cD$ be the underlying division algebra of the corestriction $cor_{L/F} (D)$ of D. We show that the index $ind(^cD) of ^cD$ divides $[Z(\overline{D}) : Z(\overline {^cD})] \cdot ind(D), where Z(\overline{D})$ is the center of the residue division ring $\overline{D}$.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.13 no.4
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• pp.179-191
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• 2013

The quincunx lattice is a non-separable sampling method in image processing. It treats the different directions more homogeneously and good frequency property than the separable two dimensional schemes. The high density discrete wavelet transformation is one that expands an N point signal to M transform coefficients with M > N. In two dimensions, this transform outperforms the standard discrete wavelet transformation in terms of shift-invariant. Although the transformation utilizes more wavelets, sampling rates are high costs. This paper proposed the high density discrete wavelet transform using quincunx sampling, which is a discrete wavelet transformation that combines the high density discrete transformation and non-separable processing method, each of which has its own characteristics and advantages. Proposed wavelet transformation can service good performance in image processing fields.

• Proceedings of the IEEK Conference
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• 1998.10a
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• pp.1157-1160
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• 1998

This paper describes the design of a block data flow architecture(BDFA) which implements 2-D discrete wavelet transform(DWT)/inverse discrete wavelet transform(IDWT) for real time image processing applications. The BDFA uses 2-D product separable filters for DWT/IDWT. It consists of an input module, a processor array, and an output module. It use both data partitioning and algorithm partitioning to achieve high efficiency and high throughput. The 2-D DWT/IDWT algorithm for 256$\times$256 lenna image has been simulated using IDL(Interactive Data Language). The 2-D array structured BDFA for the 2-D filter has been modeled and simulated using VHDL.

• Journal of the Korean Ceramic Society
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• v.34 no.8
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• pp.886-896
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• 1997

To investigate an effect of phase separation on precipitation characteristics of CuCl nanocrystals in CuCl doped nonlinear optical glasses, borosilicate glass systems with 9 different compositions with ~2wt% of CuCl were selected and CuCl doped glasses were prepared by melting and precipitation method. Microstructural properties of the CuCl doped glasses were analyzed by optical absorption spectroscopy, acid elution test, TEM, and EDXS. While phase separation did not occur in Glass A~D, interconnected and droplet microstructures due to phase separation were found in Glass E, F and Glass G~I, respectively. In the particular composition of the matrix glasses in this study, the precipitation of the CuCl particles was observed in the phase separable glasses, not in phase non-separable glasses. The CuCl particles were precipitated in both silica-rich phase region and boronrich phase region of the glass matrix. In the case of 7.7Na2O-36.6B2O3-52.7SiO2(mole%) glass, the larger CuCl particles than those in the silica-rich phase region were observed in the boron-rich phase region.

• Journal of the Korean Statistical Society
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• v.14 no.2
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• pp.87-94
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• 1985

This paper extends the results of Ellis and Rosen (1982 a) to some more general integrals and applies our main theorem to compute the specific free energy of some models in statistical mechanics. The general integrals of this paper mean the integrals with respect to the probability measures induced by the sample mean of n i.i.d. random variables taking values in a separable Banach space.

• Proceedings of the IEEK Conference
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• 2000.07a
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• pp.278-281
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• 2000

Matching pursuit algorithm is a signal expansion technique whose efficiency for motion compensated residual image has already been demonstrated in the MPEG-4 framework. However, one of the practical concerns related to applying matching pursuit algorithm to real-time scalable video coding is its massive computation required for finding dictionary elements. In this respective, this paper proposes a fast algorithm, which is composed of three sub-methods. The first method utilizes the property of symmetry in 1-D dictionary element and the second uses mathematical elimination of inner product calculation in advance, and the last one uses frequency property of 2-D dictionary. Experimental results show that our algorithm needs about 30% computational load compared to the conventional fast algorithm using separable property of 2-D gabor dictionary with negligible quality degradation.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.21 no.5
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• pp.1123-1131
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• 1996

Several improved quadrature polar separable (QPS) filters have been proposed and applied in texture processing since Knutsson proposed the QPS filter. They include a Knutsson's cosine function or oan exponential attenuation function, as the orientational function, and a Knutsson's exponential function or a finite prolate spheroidal sequence (FPSS) or an asymptotic FPSS, as the radial weighting functions. They represent different properties in terms of the generation of texture images, the orientational estimation, and the segmentation of synthetic texture image. In this paper, we have constructed several kernal functions for the 2-D QPS filter and analyzed their properties. A series of experiments have been carried out in order to estimate the frequency components and orientational angles of a local texture in Fourier domain. finally some problems encountered in applying QPS filters to feature description and segmentation are considered. Experimental results show that the improved Knutsson's filter and the asymptotic FPSS filter are useful in terms of the orientational estimation and the sementation of synthetic texture image.

• International Journal of Computer Science & Network Security
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• v.22 no.9
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• pp.175-182
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• 2022

In our daily life, we come across different types of information, for example in the format of multimedia and text. We all need different types of information for our common routines as watching/reading the news, listening to the radio, and watching different types of videos. However, sometimes we could run into problems when a certain type of information is required. For example, someone is listening to the radio and wants to listen to jazz, and unfortunately, all the radio channels play pop music mixed with advertisements. The listener gets stuck with pop music and gives up searching for jazz. So, the above example can be solved with an automatic audio classification system. Deep Learning (DL) models could make human life easy by using audio classifications, but it is expensive and difficult to deploy such models at edge devices like nano BLE sense raspberry pi, because these models require huge computational power like graphics processing unit (G.P.U), to solve the problem, we proposed DL model. In our proposed work, we had gone for a low complexity model for Audio Event Detection (AED), we extracted Mel-spectrograms of dimension 128×431×1 from audio signals and applied normalization. A total of 3 data augmentation methods were applied as follows: frequency masking, time masking, and mixup. In addition, we designed Convolutional Neural Network (CNN) with spatial dropout, batch normalization, and separable 2D inspired by VGGnet [1]. In addition, we reduced the model size by using model quantization of float16 to the trained model. Experiments were conducted on the updated dataset provided by the Detection and Classification of Acoustic Events and Scenes (DCASE) 2020 challenge. We confirm that our model achieved a val_loss of 0.33 and an accuracy of 90.34% within the 132.50KB model size.