• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2009.04a
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• pp.326-331
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• 2009

An algorithm is proposed for computing dynamic displacements of a bridge using FBG sensors. An existing algorithm for estimating dynamic displacements of a simply supported beam through mode superposition is extended and applied to various types of bridges with bending and torsional modes. The proposed algorithm is examined through field tests on a suspension span steel deck plate box girder bridge. Guidelines are provided for determining the number of modes and the number of strain gages to be used.

• Proceedings of the IEEK Conference
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• 2003.11c
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• pp.55-59
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• 2003

In this paper, we estimate the performance requirements of general-purpose DSP for Carrier Recovery of OFDM DVB-T receiver. Firstly, we transported the designed fixed-point OFDM DVB-T model to a floating-point software model written in C. Then, we measured the number of instruction cycles required for operation of Carrier Recovery in time. We use SignalMaster$\^$TM/ DSP platform of LYRtech Inc. as a environment of estimation, and Simulink$\^$TM/ as a graphical interface, Code Composer StudioTM of TI as profiler and compiler, and SPW$\^$TM/ for presenting functional reliability and comparing the performance distortion with fixed-point model. As a result, we show the required number of DSPs in our DSP-based system, and introduce the need of Multi-DSP-based system.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.42 no.1
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• pp.17-27
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• 2005

In this paper, we introduce a Parallel Interference Canceller (PIC) based sorting method to improve performance in the MC-DS/CDMA environment. A conventional PIC estimates and subtracts out all of the MAI (Multiple Access Interference) for each user in parallel. The parallel process ensures the low delay for the detection of all users. Also this scheme requires more stages for having better performance. Since the performance of PIC is strongly related to the correct MAI estimation, we introduce the IC (Interference Cancellation) scheme to estimate the accurate weaker signal group than the desired signal using conventional PIC. The principle of the proposed receiver sorts in descending order by the strength of signal and subtracts the MAI of the strong interferers from the desired signal for the accurate estimate of the weaker signals. Following this, the proposed scheme cancels out the improved weaker interference from the desired signal, using the output of the pre-step. In this result, the proposed system obtains better BER performance than the conventional PIC because the accuracy of the strong signal is improved. However, a disadvantage exists in that the processing time has slightly longer delay than the PIC owing to the power sorting and the MAI estimation process. The system performance evaluates and compares other non-liner It according to the number of sub-carriers in the limited-bandwidth.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.47 no.1
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• pp.150-158
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• 2010

Filtering is necessary for the SRC(sample rate converter), that is used to change the sampling rate of a digital signal. The larger the conversion ratio of the sampling rate becomes, the more signal processing is needed for the filter, which means more complexity on realization. Thus it is important to reduce the amount of signal processing for the case of substantial conversion ratios. In this paper it is presented an efficient design method of a multistage FIR(finite impulse response) filter, with which the rate conversion occurs in stages rather than in one step. In this method, filter searching is performed exhaustively over all possible factorization of the conversion ratio, and also the filter complexity is measured based on direct realization rather than on estimation. It has been shown a designed multistage filter to have a less number of multiplications for filtering operation in comparison with a conventionally designed one. It has also been found that by allowing some variations of the filter architecture such as a halfband filter or a filter with multiple transition bands, the number of multiplications can be reduced further.

• Journal of Communications and Networks
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• v.12 no.4
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• pp.289-307
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• 2010

The problem of model selection arises in a number of contexts, such as subset selection in linear regression, estimation of structures in graphical models, and signal denoising. This paper studies non-asymptotic model selection for the general case of arbitrary (random or deterministic) design matrices and arbitrary nonzero entries of the signal. In this regard, it generalizes the notion of incoherence in the existing literature on model selection and introduces two fundamental measures of coherence-termed as the worst-case coherence and the average coherence-among the columns of a design matrix. It utilizes these two measures of coherence to provide an in-depth analysis of a simple, model-order agnostic one-step thresholding (OST) algorithm for model selection and proves that OST is feasible for exact as well as partial model selection as long as the design matrix obeys an easily verifiable property, which is termed as the coherence property. One of the key insights offered by the ensuing analysis in this regard is that OST can successfully carry out model selection even when methods based on convex optimization such as the lasso fail due to the rank deficiency of the submatrices of the design matrix. In addition, the paper establishes that if the design matrix has reasonably small worst-case and average coherence then OST performs near-optimally when either (i) the energy of any nonzero entry of the signal is close to the average signal energy per nonzero entry or (ii) the signal-to-noise ratio in the measurement system is not too high. Finally, two other key contributions of the paper are that (i) it provides bounds on the average coherence of Gaussian matrices and Gabor frames, and (ii) it extends the results on model selection using OST to low-complexity, model-order agnostic recovery of sparse signals with arbitrary nonzero entries. In particular, this part of the analysis in the paper implies that an Alltop Gabor frame together with OST can successfully carry out model selection and recovery of sparse signals irrespective of the phases of the nonzero entries even if the number of nonzero entries scales almost linearly with the number of rows of the Alltop Gabor frame.

• Journal of Welding and Joining
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• v.11 no.2
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• pp.27-41
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• 1993

The estimation of nugget sizes was attempted by utilizing the artificial neural networks method. Artificial neural networks is a highly simplified model of the biological nervous system. Artificial neural networks is composed of a large number of elemental processors connected like biological neurons. Although the elemental processors have only simple computation functions, because they are connected massively, they can describe any complex functional relationship between an input-output pair in an autonomous manner. The electrode head movement signal, which is a good indicator of corresponding nugget size was determined by measuring the each test specimen. The sampled electrode movement data and the corresponding nugget sizes were fed into the artificial neural networks as input-output pairs to train the networks. In the training phase for the networks, the artificial neural networks constructs a fuctional relationship between the input-output pairs autonomusly by adjusting the set of weights. In the production(estimation) phase when new inputs are sampled and presented, the artificial neural networks produces appropriate outputs(the estimates of the nugget size) based upon the transfer characteristics learned during the training mode. Experimental verification of the proposed estimation method using artificial neural networks was done by actual destructive testing of welds. The predicted result by the artifficial neural networks were found to be in a good agreement with the actual nugget size. The results are quite promising in that the real-time estimation of the invisible nugget size can be achieved by analyzing the process variable without any conventional destructive testing of welds.

• The KIPS Transactions:PartB
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• v.9B no.2
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• pp.199-204
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• 2002

Since motion estimation and motion compensation methods remove the redundant data to employ the temporal redundancy in images, it plays an important role in digital video compression. Because of its high computational complexity, however, it is difficult to apply to high-resolution applications in real time environments. If we have information about the motion of an image block before the motion estimation, the location of a better starting point for the search of an exact motion vector can be determined to expedite the searching process. In this paper, we present an adaptive motion estimation approach bated on temporal correlations of consecutive image frames that defines the search pattern and determines the location of the initial search point adaptively. Through experiments, compared with DS(Diamond Search) algorithm, the proposed algorithm is about 0.1∼0.5(dB) better than DS in terms of PSNR(Peak Signal to Noise Ratio) and improves as high as 50% compared with DS in terms of average number of search point per motion vector estimation.

• 한국해양학회지
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• v.24 no.4
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• pp.172-183
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• 1989

Acoustical estimation of vertical distributions of zooplankton was carried out by using the backscattered signals of ADCP which was deployed in the Korea Strait in September, 1978. the backscattered signals of ADCP represents the total backward sound intensity caused by the scatters existing within the insonified water column of 8m deep. Based on these backscattered intensities, the estimated number of individual zooplankton (namely, Copepods) varies with depth such that in the surface layer above the thermocline, the numbers are exceedingly larger than the lower layer. It is also shown that a relatively larger number of individuals exists in the bottom cold water layer in the centeral part of the Strait. The horizontal distribution of the zooplankton in the surface layer across the west channel of the Strait shows that the number is higher in the coastal zone of the Korea and it decreases toward the central and then remains constant up to the vicinity of the Tsushima Island where it increases again. This type of distributions is well fitted to the one obtained at several stations by the conventional method at least in qualitative way. Therefore, it is quite plausible to use the ADCP data for monitoring the spatial and temporal distributions of zooplankton.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.25 no.3
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• pp.372-375
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• 2014

A monopulse based on maximum likelihood(ML) in jamming scenario can suppress jamming signal using an inverse matrix of a covariance matrix. In order to achieve adequate suppression of jamming signal, the sufficient number of snapshots is required. However, this is not possible in high PRF scenario, which hinders a real-time tracking. Moreover, even with the large number of snapshots, the estimation accuracy of the target direction is decreased in low JNR(Jammer to Noise Ratio) due to insufficient jammer suppression. In this paper, we propose a monopulse algorithm that doesn't degrade performance significantly with a small number of snapshots and in low JNR. We show its derivation that exploits noise-jammer subspace of a covariance matrix, along with its performance through simulation.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.48 no.4
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• pp.6-14
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• 2011

The fast growing of the number of users requires the development of reliable communication systems able to provide higher data rates. In order to meet those requirements, techniques such as Multiple Input Multiple Out (MIMO) and Orthogonal Frequency Division multiplexing (OFDM) have been developed in the recent years. In order to combine the benefits of both techniques, the research activity is currently focused on MIMO-OFDM systems. In addition, for a fast wireless channel environment, the data rate and reliability can be optimized by setting the modulation and coding adaptively according to the channel conditions; and using sub-carrier frequency, and power allocation techniques. Depending on how accurate the feedback-based system obtain the channel state information (CSI) and feed it back to the transmitter without delay, the overall system performance would be poor or optimal. In this paper, we propose a Signal to Noise Ratio (SNR) estimation algorithm where the preamble is known for both sides of the transciever. Through simulations made over several channel environments, we prove that our proposed SNR estimation algorithm is more accurate compared with the traditional SNR estimation. Also, We applied AMC on several channel environments using the parameters of IEEE 802.11n, and compared the Throughput performance when using each of the different SNR Estimation Algorithms. The results obtained in the simulation confirm that the proposed algorithm produces the highest Throughput performance.