• The Journal of the Acoustical Society of Korea
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• v.33 no.3
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• pp.216-224
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• 2014

In this paper, we propose a new method to drastically reduce computational complexity in Gaussian Mixture Model (GMM)-based Speaker Identification (SI). Generally, GMM-based SI systems have very high computational complexity proportional to the length of the test utterance, the number of enrolled speakers, and the GMM size. These make the SI systems difficult to be used in various real applications in spite of their broad applicability. Thus, a trade-off between computational complexity and identification accuracy is considered as a primary issue for practical applications. In order to reduce computational complexity sharply with a little loss of accuracy, we introduce a method based on the Universal Background Model (UBM) clustering approach and then we show that it can be used successfully in real-time applications. In experiments with the proposed algorithm, we obtained a speed-up factor of 6 with a negligible loss of accuracy.

• The Journal of the Korea institute of electronic communication sciences
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• v.17 no.6
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• pp.1055-1062
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• 2022

In order to use the Massive MIMO (Multi Input Multi Output) technology using the massive array antenna, it is essential to know the angle of arrival (AOA) of the signal. When using a massive array antenna, the existing AOA estimation algorithm has excellent estimation performance, but also has a disadvantage in that computational complexity increases in proportion to the number of antenna elements. To solve this problem, a cascade AOA estimation algorithm has been proposed and the performance of a single-shaped (non)massive array antenna has been proven through a number of papers. However, the computational complexity of the cascade AOA estimation algorithm to which single and double rim array antennas are applied has not been compared. In this paper, we compare and analyze the computational complexity for AOA estimation when single and double rim array antennas are applied to the cascade AOA estimation algorithm.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.8A
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• pp.583-591
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• 2009

OFDM(orthogonal frequency division multiplexing) signal with high PAPR(peak to average power ratio) produces the nonlinear distortion and/or decreases down the power efficiency of HPA(high power amplifier). So, the IMD(inter-modulation distortion) reduction method was proposed to reduce the nonlinear distortion, which shows better BER(bit error rate) performance than the PAPR reduction methods. However, IMD reduction method has inherent problem which system complexity and processing time increases because the FFT(fast Fourier transform) processor is added in transmitter and decision criterion of IMD reduction method is computed in frequency domain,. In this paper, therefore, we propose a new IMD reduction method to reduce the computational complexity and structure of IMD computation. And we apply this proposed method into OFDM system using PTS(partial transmit sequence) scheme and compare the computational complexity between conventional and proposed IMD reduction method. This method can reduce the system size and computational complexity. Also, the proposed has almost same BER performance with the conventional IMD reduction method.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.31 no.4C
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• pp.303-309
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• 2006

By combining the space-time diversity technique and iterative turbo codes, space-time turbo codes(STTCS) are able to provide powerful error correction capability. However, the multi-path transmission and iterative decoding structure of STTCS make the decoder very complex. In this paper, we propose a low complexity decoder, which can be used to decode STTCS as well as general iterative codes such as turbo codes. The efficient implementation of the backward recursion and the log-likelihood ratio(LLR) update in the proposed algorithm improves the computational efficiency. In addition, if we approximate the calculation of the joint LLR by using the approximate ratio(AR) algorithm, the computational complexity can be reduced even further. A complexity analysis and computer simulations over the Rayleigh fading channel show that the proposed algorithm necessitates less than 40% of the additions required by the conventional Max-Log-MAP algorithm, while providing the same overall performance.

• ETRI Journal
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• v.25 no.5
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• pp.345-355
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• 2003

In this paper, we propose a method for designing a class of M-channel, causal, stable, perfect reconstruction, infinite impulse response (IIR), and parallel uniform discrete Fourier transform (DFT) filter banks. It is based on a previously proposed structure by Martinez et al. [1] for IIR digital filter design for sampling rate reduction. The proposed filter bank has a modular structure and is therefore very well suited for VLSI implementation. Moreover, the current structure is more efficient in terms of computational complexity than the most general IIR DFT filter bank, and this results in a reduced computational complexity by more than 50% in both the critically sampled and oversampled cases. In the polyphase oversampled DFT filter bank case, we get flexible stop-band attenuation, which is also taken care of in the proposed algorithm.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.21 no.5
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• pp.1109-1122
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• 1996

Generally, moving images contain the various components in motions, which reange from a static object and background to a fast moving object. To extract the accurate motion parameters, we must consider the various motions. That requires a wide search egion in motion estimation. The wide search, however, causes a high computational complexity. If we have a few knowledge about the motion direction and magnitude before motion estimation, we can determine the search location and search window size using the already-known information about the motion. In this paper, we present a local adaptive motion estimation approach that predicts a block motion based on spatio-temporal neighborhood blocks and adaptively defines the search location and search window size. This paper presents a technique for reducing computational complexity, while having high accuracy in motion estimation. The proposed algorithm is introduced the forward and backward projection techniques. The search windeo size for a block is adaptively determined by previous motion vectors and prediction errors. Simulations show significant improvements in the qualities of the motion compensated images and in the reduction of the computational complexity.

• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.3
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• pp.139-143
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• 2014

This paper proposes a simplified DC calculation method for simplified depth coding (SDC) mode of 3D High Efficiency Video Coding (3D-HEVC) to reduce the computational complexity. For the computational complexity reduction, the current reference software of 3D-HEVC employs reference samples sub-sampling method. However, accumulation, branch, and division operations are still utilized and these operations increase computational complexity. The proposed method calculates DC value without those operations. The experimental results show that the proposed method achieves 0.1% coding gain for synthesized views in common test condition (CTC) with the significantly reduced number of computing operations.

• Proceedings of the KIEE Conference
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• 2007.04a
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• pp.20-22
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• 2007

The H.264/AVC standard developed by the joint Video Team (JVT) provides better coding efficiency than previous standards. The new emerging H.264/AVC employs variable block size motion estimation using multiple reference frame with 1/4-pel MV(Motion Vector) accuracy. These techniques are a important feature to accomplish higher coding efficiency. However, these techniques are increased overall computational complexity. To overcome this problem, this paper proposes advanced fast mode decision suited for variable block size by classifying inter mode based on Rate Distortion Optimization(RDO) technique. Proposed algorithm is going to use to implement H/W structure for fast mode decision. The experimental results shows that the proposed algorithm provides significant reduction computational complexity without any noticeable coding loss and additional computation. Entire computational complexity is decreased about 30%.

• Journal of Korea Multimedia Society
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• v.21 no.1
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• pp.18-25
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• 2018

In High Efficiency Video Coding (HEVC), integer motion estimation (IME) requires a large amount of computational complexity because HEVC adopts the high flexible and hierarchical coding structures. In order to reduce the computational complexity of IME, this paper proposes the search range reduction algorithm, which takes advantage of motion vectors similarity between different layers. It needs only a few modification for HEVC reference software. Based on the experimental results, the proposed algorithm reduces the processing time of IME by 28.1% on average, whereas its the $Bj{\emptyset}ntegaard$ delta bitrate (BD-BR) increase is 0.15% which is negligible.

• Journal of Korea Society of Digital Industry and Information Management
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• v.4 no.2
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• pp.49-55
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• 2008

Combining OFDMA with MIMO is the key technology for the 4G mobile communication. OFDMA can relieve inherent difficulties of high-speed transmission. MIMO technology can be largely categorized into two techniques: one is STC for diversity gain and the other is SM for high frequency efficiency. In this paper, we depict various MIMO techniques of two transmit antenna and compare the computational complexity of decoding process for the techniques. Then, we analysis the performance of the techniques in the WiBro downlink environment based on OFDMA. We perfer ML algorithm which is the optimum performance and ZF algorithm of least computational complexity for SM detection.