• Journal of the Korean Society for Industrial and Applied Mathematics
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• v.12 no.1
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• pp.41-53
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• 2008

Polynomials are one of most important and widely used numerical tools in dealing with a smooth function on a bounded domain and trigonometric functions work for smooth periodic functions. However, they are not the best choice if a function has a bounded support in space and in frequency domain. The Prolate Spheroidal wave function (PSWF) of order zero has been known as a best candidate as a basis for band-limited functions. In this paper, we review some basic properties of PSWFs defined as eigenfunctions of bounded Fourier transformation. We also propose numerical inversion schemes based on PSWF and present some numerical examples to show their feasibilities as signal processing tools.

• International Journal of Precision Engineering and Manufacturing
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• v.9 no.4
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• pp.45-50
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• 2008

The Fourier-Mellin transform is the theoretical basis for the translation, rotation, and scale invariance of an image. However, its implementation requires a log-polar map of the original image, which requires logarithmic sampling of a radial variable in that image. This means that the mapping process is accompanied by considerable loss of data. To solve this problem, we propose a dual log-polar map that uses both a forward image map and a reverse image map simultaneously. Data loss due to the forward map sub-sampling can be offset by the reverse map. This is the first step in creating an invertible log-polar map. Experimental results have demonstrated the effectiveness of the proposed scheme.

• Journal of Communications and Networks
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• v.13 no.5
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• pp.449-455
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• 2011

Inspired by fast Jacket transforms, we propose simple factorization and construction algorithms for the M-dimensional discrete Fourier transform (DFT) matrices underlying generalized Chinese remainder theorem (CRT) index mappings. Based on successive coprime-order DFT matrices with respect to the CRT with recursive relations, the proposed algorithms are presented with simplicity and clarity on the basis of the yielded sparse matrices. The results indicate that our algorithms compare favorably with the direct-computation approach.

• Proceedings of the KSRS Conference
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• 2008.10a
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• pp.169-172
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• 2008

Land-use or land-cover classification of satellite images is one of the important tasks in remote sensing application and many researchers have been tried to enhance classification accuracy. Previous studies show that the classification technique based on wavelet transform is more effective than that of traditional techniques based on original pixel values, especially in complicated imagery. Various wavelets can be used in wavelet transform. Wavelets are used as basis functions in representing other functions, like sinusoidal function in Fourier analysis. In these days, some basis functions such as Haar, Daubechies, Coiflets and Symlets are mainly used in 2D image processing. Selecting adequate wavelet is very important because different results could be obtained according to the type of basis function in classification. However, it is not easy to choose the basis function which is effective to improve classification accuracy. In this study, we computed the wavelet coefficients of satellite image using 10 different basis functions, and then classified test image. After evaluating classification results, we tried to ascertain which basis function is the most effective for image classification. We also tried to see if the optimum basis function is decided by energy parameter before classifying the image using all basis function. The energy parameter of signal is the sum of the squares of wavelet coefficients. The energy parameter is calculated by sub-bands after the wavelet decomposition and the energy parameter of each sub-band can be a favorable feature of texture. The decision of optimum basis function using energy parameter in the wavelet based image classification is expected to be helpful for saving time and improving classification accuracy effectively.

• Journal of the Institute of Electronics and Information Engineers
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• v.53 no.6
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• pp.167-173
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• 2016

Compressed Sensing(CS) is the theory that can recover signals which are sampled below the Nyquist sampling rate to original analog signals. In this paper, we propose the estimation algorithm of ultrasonic attenuation coefficients in the frequency domain using CS. While most estimation algorithms transform the time-domain signals into the frequency-domain using the Fourier transform, the proposed method directly utilize the spectral information in the recovery process by the basis matrix without the completely recovered signals in the time domain. We apply three transform bases for sparsifying and estimate the attenuation coefficients using the Centroid Downshift method with Dual-reference diffraction compensation technique. The estimation accuracy and execution time are compared for each basis matrix. Computer simulation results show that the DCT basis matrix exhibits less than 0.35% estimation error for the compressive ratio of 50% and about 6% average error for the compressive ratio of 70%. The proposed method which directly extracts frequency information from the CS signals can be extended to estimating for other ultrasonic parameters in the Quantitative Ultrasound (QUS) Analysis.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.29 no.5
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• pp.543-550
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• 2011

The gravity anomaly is a basic geophysical data applied in various fields such as geophysics, geodesy and national defense. In general, the gravity anomaly is used through a interpolation process based on the constructed database. The gravity variation, however, is appeared in various shapes depending on the topography and the density of the underground structures. Therefore, the interpolation could lead to a large differences if the gravity fields do not satisfy the assumptions on the signal behavior like linear or a certain degree polynomials. Furthermore, the interpolation does not reflect the physical characteristics of the gravity such as the harmonic condition. In this study, the gravity modeling using the plane Fourier series and radial basis functions are performed to overcome the problems in the usual interpolation. The results of the modeling is analyzed for the case of the gravity referenced navigation focused on the signal characteristics. Based on the study, it was found that the results from modeling are not much different to that from the interpolation in a smoothly varied area. In case of the highly varied area, however, a large differences are appeared among the three methods. Especially, the Fourier series shows the most smooth variations in the modeled gravity values while the highest variations appeared in the interpolation. Applying to the gravity referenced navigation, it was found that the modeling is more effective in calculation cost. It is considered that the results from this study provides a basis on effective modeling of the gravity fields in terms of the signal characteristics and resolution for various application fields.

• Bulletin of the Korean Mathematical Society
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• v.49 no.5
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• pp.939-947
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• 2012

In this paper, we give a generalization of the embeddings of Riemannian manifolds via their heat kernel and via a finite number of eigenfunctions. More precisely, we embed a family of Riemannian manifolds endowed with a time-dependent metric analytic in time into a Hilbert space via a finite number of eigenfunctions of the corresponding Laplacian. If furthermore the volume form on the manifold is constant with time, then we can construct an embedding with a complete eigenfunctions basis.

• Bulletin of the Korean Chemical Society
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• v.16 no.3
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• pp.281-284
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• 1995

The visible emission spectra of the o-xylyl radical in the gas phase have been obtained using a Fourier transform spectrometer coupled with a technique of supersonic expansion. The o-xylyl radical was generated in a jet by expansion with an inert buffer gas He from a high voltage dc discharge of the precursor o-xylene. The spectra were analyzed on the basis of the rotational contours of the vibronic bands as well as the known vibrational frequencies by a matrix isolation method.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.21 no.1
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• pp.214-223
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• 1996

Noise effects on image profiles reconstructed by the spectral inverse scattering technique is studied based on moment method with series-expanded basis function. It is found that the Fourier series expansion to the field distribution and the averaging of the reconstructed profile in each enlarged cell provides an effective tool for the reduction of noise effects.

• The Bulletin of The Korean Astronomical Society
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• v.46 no.2
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• pp.44.1-44.1
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• 2021

The Cosmic Microwave Background (CMB) contains a wealth of information about the perturbations in the early universe. Its bispectrum, the Fourier counterpart of three-point correlation functions, is a direct probe of primordial non-Gaussianity predicted by many physically well motivated inflation models. Motivated by the substantial improvement in sensitivity expected from future CMB surveys, we developed a novel bispectrum estimator capable of handling such high-resolution data. Our code, named CMB-BEst, utilises a set of separable basis functions to constrain a wide variety of models simultaneously. Flexibility in the choice of basis enables targeted analysis on highly oscillatory inflation models, which are previously unconstrained due to the numerical and computational challenges involved. We present the results of our thorough validation tests, both internal and against conventional approaches. We provide a proof-of-concept example with Planck satellite data and sketch out the road ahead.