• Communications for Statistical Applications and Methods
• /
• v.18 no.1
• /
• pp.79-87
• /
• 2011

A spatial time series model was used for analyzing the method of spatial time series (not the ARIMA model that is popular for analyzing spatial time series) by using chicken pox data which is a highly contagious disease and grid data due to ARIMA not reflecting the spatial processes. Time series model contains a weighting matrix, because that spatial time series model influences the time variation as well as the spatial location. The weighting matrix reflects that the more geographically contiguous region has the higher spatial dependence. It is hypothesized that the weighting matrix gives neighboring areas the same influence in the study of the spatial time series model. Therefore, we try to present the conclusion with a weighting matrix in a way that gives the same weight to existing neighboring areas in the study of the suitability of the STARMA model, spatial time series model and STBL model, in the comparative study of the predictive power for statistical inference, and the results. Furthermore, through the Kalman-Filter method we try to show the superiority of the Kalman-Filter method through a parameter assumption and the processes of prediction.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.22 no.4
• /
• pp.515-520
• /
• 2012

In brain computer interface (BCI) system, the most important part is classification of human thoughts in order to translate into commands. The more accuracy result in classification the system gets, the more effective BCI system is. To increase the quality of BCI system, we proposed to reduce noise and artifact from the recording data to analyzing data. We used auditory stimuli instead of visual ones to eliminate the eye movement, unwanted visual activation, gaze control. We applied independent component analysis (ICA) algorithm to purify the sources which constructed the raw signals. One of the most famous spatial filter in BCI context is common spatial patterns (CSP), which maximize one class while minimize the other by using covariance matrix. ICA and CSP also do the filter job, as a raw filter and refinement, which increase the classification result of linear discriminant analysis (LDA).

• Smart Structures and Systems
• /
• v.16 no.6
• /
• pp.1049-1068
• /
• 2015

In the paper, the authors propose the application of operational deflection shapes (ODS) for the detection of structural changes in technical objects. The ODS matrix is used to formulate the spatial filter that is further used for damage detection as a classical modal filter (Meirovitch and Baruh 1982, Zhang et al. 1990). The advantage of the approach lies in the fact that no modal analysis is required, even on the reference spatial filter formulation and other components apart from structural ones can be filtered (e.g. harmonics of rotational velocity). The proposed methodology was tested experimentally on a laboratory stand, a frame-like structure, excited from two sources: an impact hammer, which provided a wide-band excitation of all modes, and an electro-dynamic shaker, which simulated a harmonic component in the output spectra. The damage detection capabilities of the proposed method were tested by changing the structural properties of the model and comparing the results with the original ones. The quantitative assessment of damage was performed by employing a damage index (DI) calculation. Comparison of the output of the ODS filter and the classical modal filter is also presented and analyzed in the paper. The closing section of the paper describes the verification of the method on a real structure - a road viaduct.

• Proceedings of the KIEE Conference
• /
• 2004.11c
• /
• pp.178-180
• /
• 2004

In this work, we propose new method of sigma filtering for efficient filtering and preserving edge regions in DCT Domain. In block-based image compression technique, the image is first divided into non-overlapping $8{\times}8$ blocks. Then, the two-dimensional DCT is computed for each $8{\times}8$ block. Once the DCT coefficients are obtained, they are quantized using a specific quantization table. Quantization of the DCT coefficients is a lossy process, and in this step, noise is added. In this work, we combine IDCT matrix and filter matrix to a new matrix to simplify filtering process to remove noise after IDCT in spatial domain, for each $8{\times}8$ DCT coefficient block, we determine whether this block is edge or homogeneous region. If this block is edge region, we divide this $8{\times}8$ block into four $4{\times}4$ sub-blocks, and do filtering process for sub-blocks which is homogeneous region. By this process, we can remove blocking artifacts efficiently preserving edge regions at the same time.

• Transactions of the Korean Society for Noise and Vibration Engineering
• /
• v.18 no.6
• /
• pp.598-605
• /
• 2008

An improved beamforming method is proposed to measure the surface impedance of absorbing materials in a free field. It is possible to estimate the surface impedance by decomposing measured signals into incident and reflected signals by using the spatial filter matrix of the beamforming method. Wavelet do-noising techniques which reduce the white Gaussian noise are applied to improve the results. Phase calibration method is also used to improve the results of the measured surface impedance in a low frequency range. The results of the normal incidence experiments that are performed in a semi-anechoic chamber are verified by comparing with those of the standard test method that is presented in ASTM E1050. The proposed method is found to be reliable to measure the surface impedance for frequencies higher than 400 Hz.

• Journal of Positioning, Navigation, and Timing
• /
• v.5 no.1
• /
• pp.1-9
• /
• 2016

Range-based wireless localization system must measure accurate range between a mobile node (MN) and reference nodes. However, non-line-of-sight (NLOS) error caused by the spatial structures disturbs the localization system obtaining the accurate range measurements. Localization methods using the range measurements including NLOS error yield large localization error. But filter-based localization methods can provide comparatively accurate location solution. Motivated by the accuracy of the filter-based localization method, a filter residual-based NLOS error estimation method is presented in this paper. Range measurement-based residual contains NLOS error. By considering this factor with NLOS error properties, NLOS error is mitigated. Also a process noise covariance matrix tuning method is presented to reduce the time-delay estimation error caused by the single dynamic model-based filter when the speed or moving direction of a MN changes, that is the used dynamic model is not fit the current dynamic of a MN. The presented methods are evaluated by simulation allowing direct comparison between different localization methods. The simulation results show that the presented filter is more accurate than the iterative least squares- and extended Kalman filter-based localization methods.

• Journal of the Institute of Electronics Engineers of Korea TC
• /
• v.40 no.11
• /
• pp.1-9
• /
• 2003

The electromagnectic modal analysis method for the multiscreen structure with periodic slot array with including conductor thickness effect is presented. The multiscreen structure is seen to be exactly equivalent to a microwave guide closed by phase-shift walls. From this viewpoint, the entire generalized scattering matrix of the multiscreen structure is calculated by the cascade connection of the scattering matrices obtained by the modal analysis at guide junctions and the transmission matrices of guide region. The present method is verified in comparison with the results calculated by the previous method of moment for single screen structure. As an application example of the present method, the spatial filter having multiscreen structure is designed and the interesting characteristics such as transmission and reflection coefficient versus frequency & angle are investigated.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.34 no.5C
• /
• pp.527-539
• /
• 2009

In this paper, we propose an asynchonous ICI (Inter-Cell Interference) mitigation techniques for 3GPP LTE MIMO-OFDMA down-link receiver. An increasing in symbol timing misalignments may occur relative to sychronous network as the result of BS (Base Station) timing differences. Such symbol synchronization errors that exceed the guard interval or the cyclic prefix duration may result in MAI (Multiple Access Interference) for other carriers. In particular, at the cell boundary, this MAI becomes a critical factor, leading to degraded channel throughput and severe asynchronous ICI. Hence, many researchers have investigated the interference mitigation method in the presence of asynchronous ICI and it appears that the knowledge of the SCM (Spatial Covariance Matrix) of the asynchronous ICI plus background noise is an important issue. Generally, it is assumed that the SCM estimated by using training symbols. However, it is difficult to measure the interference statistics for a long time and training symbol is also not appropriate for MIMO-OFDMA system such as LTE. Therefore, a noise reduction method is required to improve the estimation accuracy. Although the conventional time-domain low-pass type weighting method can be effective for noise reduction, it causes significant estimation error due to the spectral leakage in practical OFDM system. Therefore, we propose a time-domain sinc type weighing method which can not only reduce the noise effectively minimizing estimation error caused by the spectral leakage but also implement frequency-domain moving average filter easily. By using computer simulation, we show that the proposed method can provide up to 3dB SIR gain compared with the conventional method.

• The Journal of the Acoustical Society of Korea
• /
• v.23 no.4
• /
• pp.288-295
• /
• 2004

Detection and localization of a slow and quiet target in shallow water environments is a challenging problem for which it is well known that snapshot is deficient because of a fast and strong interferer. This paper presents waveguide interference filtering technique that mitigate strong interferer problems in adaptive matched field processing. MCM (multiple constraint method) based on NDC (null direction constraint) has been proposed for new spatial interferer filter. MCM-NDC using replica force a interferer component to be filtered through CSDM (cross-spectral density matrix). This filtering have an effect on sidelobe reduction and restoring of signal gain of a quiet target. This technique was applied to a simulation on Pekeris waveguide and vertical array data from MAPLE03 (matched acoustic properties and localization experiment) in the East Sea and was shown to improve SBNR (signal-to-background-and-noise ratio) over the standard MVDR (minimum-variance distortionless response) and NSP (null space projection) technique.

• Journal of the Korean Society for Nondestructive Testing
• /
• v.34 no.3
• /
• pp.211-219
• /
• 2014

Closed cracks are difficult to detect using conventional ultrasonic testing because most incident ultrasound passes completely through these cracks. Nonlinear ultrasound inspection using sub-harmonic frequencies a promising method for detecting closed cracks. To implement this method, a sub-harmonic phased array (PA) is proposed to visualize the length of closed cracks in solids. A sub-harmonic PA generally consists of a single transmitter and an array receiver, which detects sub-harmonic waves generated from closed cracks. The PA images are obtained using the total focusing method (TFM), which (with a transmitter and receiving array) employs a full matrix in the observation region to achieve fine image resolution. In particular, the receiving signals are measured using a laser Doppler vibrometer (LDV) to collect PA images for both fundamental and sub-harmonic frequencies. Oblique incidence, which is used to boost sub-harmonic generation, inevitably produces various surface waves that contaminate the signals measured in the receiving transducer. Surface wave interference often degrades PA images severely, and it becomes difficult to read the closed crack's position from the images. Various methods to prevent or eliminate this interference are possible. In particular, enhancing images with signal processing could be a highly cost-effective method. Because periodic patterns distributed in a PA image are the most frequent interference induced by surface waves, spatial frequency filtering is applicable for removing these waves. Experiments clearly demonstrate that the spatial frequency filter improves PA images.