• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2012.07a
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• pp.298-301
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• 2012

This paper presents a graph-based method of detecting and tracking moving objects in H.264/SVC bitstreams for video surveillance applications that makes use the information from spatial base and enhancement layers of the bitstreams. In the base layer, segmentation of real moving objects are first performed using a spatio-temporal graph by removing false detected objects via graph pruning and graph projection, followed by graph matching to precisely identify the real moving objects over time even under occlusion. For the accurate detection and reliable tracking of moving objects in the enhancement layer, as well as saving computational complexity, the identified block groups of the real moving objects in the base layer are then mapped to the enhancement layer to provide accurate and efficient object detection and tracking in the bitstreams of higher resolution. Experimental results show the proposed method can produce reliable results with low computational complexity in both spatial layers of H.264/SVC test bitstreams.

• Korean Journal of Computational Design and Engineering
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• v.18 no.3
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• pp.167-176
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• 2013

It is necessary to construct equipment catalog in ship outfitting design and offshore plant design. The three-dimensional CAD data of equipment take on different level-of-detail depending on the purpose. Equipment suppliers provide CAD data with high complexity while ship designers need CAD data with low complexity. Therefore, it is necessary to simplify CAD data. However, it takes much time to simplify them manually. To resolve the issue, a system for automatically simplifying the 3D CAD data of equipment was developed. This paper presents the architecture of the system and the implementation details. In addition, experiment result using the prototype system is explained.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.37A no.9
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• pp.738-745
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• 2012

This paper proposes an approximated soft decision demapping algorithm with low computational complexity for coded 4+12+16 amplitude phase shift keying (APSK) in an additive white Gaussian noise (AWGN) channel. To derive the proposed algorithm, we approximate the decision boundaries for 4+12+16 APSK symbols, and then decide the log likelihood ratio (LLR) value for each bit from the approximated decision boundaries. Although the proposed algorithm shows about 0.6~1.1dB degradation on the error performance compared with the conventional max-log algorithm, it gives a significant result in terms of the computational complexity.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.37 no.6A
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• pp.480-487
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• 2012

In multicarrier code-division multiple access (MC-CDMA) systems, conventional blind channel estimation schemes require the inverse matrix calculation or eigenvalue decomposition of the received signal covariance matrix. Therefore, computational complexity of the conventional schemes is too high and they cannot be employed in downlink systems. In this paper, we propose a simple blind channel estimation scheme with very low computational complexity. Simulation results show that the proposed scheme has better channel estimation and bit error rate (BER) performance than the conventional schemes.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.5
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• pp.2299-2318
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• 2019

Location-aware networks are of great importance for both civil lives and military applications. Methods based on line-of-sight (LOS) measurements suffer sever performance loss in harsh environments such as indoor scenarios, where sensors can receive both LOS and non-line-of-sight (NLOS) measurements. In this paper, we propose a data association (DA) process based on the expectation maximization (EM) algorithm, which enables us to exploit multipath components (MPCs). By setting the mapping relationship between the measurements and scatters as a latent variable, coefficients of the Gaussian mixture model are estimated. Moreover, considering the misalignment of sensor position, we propose a space-alternating generalized expectation maximization (SAGE)-based algorithms to jointly update the target localization and sensor position information. A two dimensional (2-D) circularly symmetric Gaussian distribution is employed to approximate the probability density function of the sensor's position uncertainty via the minimization of the Kullback-Leibler divergence (KLD), which enables us to calculate the expectation step with low computational complexity. Moreover, a distributed implementation is derived based on the average consensus method to improve the scalability of the proposed algorithm. Simulation results demonstrate that the proposed centralized and distributed algorithms can perform close to the Monte Carlo-based method with much lower communication overhead and computational complexity.

• Smart Structures and Systems
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• v.15 no.3
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• pp.897-911
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• 2015

This study presents a novel approach based on advancements in Evolutionary Computation for data-driven modeling of complex multi-dimensional memory-dependent systems. The investigated example is a benchmark coupled three-dimensional system that incorporates 6 Bouc-Wen elements, and is subjected to external excitations at three points. The proposed technique of this research adapts Genetic Programming for discovering the optimum structure of the differential equation of an auxiliary variable associated with every specific degree-of-freedom of this system that integrates the imposed effect of vibrations at all other degrees-of-freedom. After the termination of the first phase of the optimization process, a system of differential equations is formed that represent the multi-dimensional hysteretic system. Then, the parameters of this system of differential equations are optimized in the second phase using Genetic Algorithms to yield accurate response estimates globally, because the separately obtained differential equations are coupled essentially, and their true performance can be assessed only when the entire system of coupled differential equations is solved. The resultant model after the second phase of optimization is a low-order low-complexity surrogate computational model that represents the investigated three-dimensional memory-dependent system. Hence, this research presents a promising data-driven modeling technique for obtaining optimized representative models for multi-dimensional hysteretic systems that yield reasonably accurate results, and can be generalized to many problems, in various fields, ranging from engineering to economics as well as biology.

• Journal of Positioning, Navigation, and Timing
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• v.11 no.1
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• pp.11-21
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• 2022

Fast Fourier transform (FFT)-based parallel acquisition techniques with reduced computational complexity have been widely used for the acquisition of binary phase shift keying (BPSK) global positioning system (GPS) signals. In this paper, we propose a low computational FFT-based fine acquisition technique, for binary offset carrier (BOC) modulated BPSK signals, that depending on the subcarrier-to-code chip rate ratio (SCR) selectively utilizes the computationally efficient frequency-domain realization of the BPSK-like technique and two-dimensional compressed correlator (BOC-TDCC) technique in the first stage in order to achieve a fast coarse acquisition and accomplishes a fine acquisition in the second stage. It is analyzed and demonstrated that the proposed technique requires much smaller mean fine acquisition computation (MFAC) than the conventional FFT-based BOC acquisition techniques. The proposed technique is one of the first techniques that achieves a fast FFT-based fine acquisition of BOC signals with a slight loss of detection probability. Therefore, the proposed technique is beneficial for the receivers to make a quick position fix when there are plenty of strong (i.e., line-of-sight) GNSS satellites to be searched.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.40 no.4
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• pp.762-768
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• 2015

D2D communication as an underlaying LTE-Advanced network has proven to be efficient in improving the network performance and decreasing the traffic load of eNodeB(enhanced NodeB). However large amount of interference can be caused by sharing the resources between the cellular users and D2D pairs. So, a resource allocation for D2D communication to coordinate the interference is necessary. Related works for resource allocation that D2D can reuse the resources of more than one cellular user with best CQI(Channel Quality Indicator) have been proposed. D2D communications may still cause interference to the primary cellular network when radio resource are shared between them. To avoid this problem, we propose a radio resource allocation algorithm with low computational complexity for D2D communication in OFDM-based wireless cellular networks. Unlike the previous works, the proposed algorithm utilizes unused ones of the whole resource. The unused resource allocate to on D2D pair can be shared only with other D2D pairs. In other words, if the distance between the D2D pairs is sufficient, we allowed more than two D2D pairs to share the same resources. The simulation results have proven that the proposed algorithm has up to 11 times lower computational complexity than the compared one according to the number of D2D.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.48 no.5
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• pp.46-54
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• 2011

In this paper, we propose a low-complexity loop filtering method depending on transform-block regions. Block adaptive loop filter (BALF) was developed to improve about 10% in compression performance for the next generation video coding. The BALF employs the Wiener filter that makes reconstructed frames close to the original ones and transmits filter-related information. However, the BALF requires high computational complexity, while it can achieve high compression performance because the block adaptive loop filter is applied to all the pixels in blocks. The proposed method is a new loop filter that classifies pixels in a block into inner and boundary regions based on the characteristics of the integer transform and derives optimum filters for each region. Then, it applies the selected filters for the inner and/or boundary regions. The decoder complexity can be adjusted by selecting region-dependent filter to be used in the decoder side. We found that the proposed algorithm can reduce 35.5% of computational complexity with 2.56% of compression loss, in case that only boundary filter is used.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.51 no.2
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• pp.86-88
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• 2002

An estimation method for the characteristic parameters in the low frequency signal is proposed in this paper. A low frequency signal is assumed to be modulated or distorted by high frequency terms. The algorithm proposed in this paper is designed to select set of local maximums in a successive manner, hence it is denoted as the iterative peak picking(IPP) algorithm. The IPP algorithm is operating in the time domain and is using only the comparison operation between two neighboring samples. Therefore, its computational complexity is very low and the delay caused by the computation is negligible, which make the real-time operation possible with economic hardware. The proposed algorithm is verified on the pitch estimation of speech signal and blood pulse estimation.