• Journal of the Institute of Electronics Engineers of Korea CI
• /
• v.45 no.6
• /
• pp.179-186
• /
• 2008

In this paper we analyse the effects of Bayesian algorithm in teaming class imbalance problems and compare the performance evaluation methods. The teaming performance of the Bayesian algorithm is evaluated over the class imbalance problems generated by priori data distribution, imbalance data rate and discrimination complexity. The experimental results are calculated by the AUC(Area Under the Curve) values of both ROC(Receiver Operator Characteristic) and PR(Precision-Recall) evaluation measures and compared according to imbalance data rate and discrimination complexity. In comparison and analysis, the Bayesian algorithm suffers from the imbalance rate, as the same result in the reported researches, and the data overlapping caused by discrimination complexity is the another factor that hampers the learning performance. As the discrimination complexity and class imbalance rate of the problems increase, the learning performance of the AUC of a PR measure is much more variant than that of the AUC of a ROC measure. But the performances of both measures are similar with the low discrimination complexity and class imbalance rate of the problems. The experimental results show 4hat the AUC of a PR measure is more proper in evaluating the learning of class imbalance problem and furthermore gets the benefit in designing the optimal learning model considering a misclassification cost.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.35 no.6C
• /
• pp.539-546
• /
• 2010

In next generation wireless communication systems based on OFDM, multiple-input multiple-output (MIMO) technique is adopted in order to achieve high data throughput with limited bandwidth. As one of MIMO techniques, spatial multiplexing scheme needs high performance data detection algorithm that can be performed with low computational complexity. In this paper, we propose an algorithm that can compute QRM-MLD with reduced complexity. Also, hybrid detection technique is proposed, which can reduce the complexity by selecting between MMSE and QRM-MLD according to the channel condition. The proposed algorithm provides the trade-off between performance and complexity. The computer simulations for downlink transmission in 3GPP LTE system show that less than 0.1dB performance degradation can be achieved at 0.1% BER with 59% reduction on computational complexity compared with the conventional QRM-MLD algorithm.

• Journal of the Institute of Electronics Engineers of Korea SD
• /
• v.45 no.6
• /
• pp.96-103
• /
• 2008

This paper proposes a new low-power and small-area Reed-Solomon decoder. The proposed Reed-Solomon decoder using a novel simplified form of the modified Euclid's algorithm can support low-hardware complexity and low-Power consumption for Reed-Solomon decoding. The simplified modified Euclid's algorithm uses new initial conditions and polynomial computations to reduce hardware complexity, and thus, the implemented architecture consisting of 3r basic cells has the lowest hardware complexity compared with existing modified Euclid's and Berlekamp-Massey architectures. The Reed-Solomon decoder has been synthesized using the $0.18{\mu}m$ Samsung standard cell library and operates at 370MHz and its data rate supports up to 2.9Gbps. For the (255, 239, 8) RS code, the gate counts of the simplified modified Euclid's architecture and the whole decoder excluding FIFO memory are only 20,166 and 40,136, respectively. Therefore, the proposed decoder can reduce the total gate count at least 5% compared with the conventional DCME decoder.

• Journal of Korea Multimedia Society
• /
• v.3 no.4
• /
• pp.347-355
• /
• 2000

This paper presents an adaptive AEC(acoustic echo canceller) based on the wavelet transform using M-channel subband QMF filter banks. The proposed algorithm improves the performance of AEC with a realtime process by a low complexity of wavelet transform filter banks, a subband processing and a orthogonality of wavelet subband filter. Adaptive filter coefficients of each subband are updated using LMS algorithm with a low complexity and a easy realization for a realtime processing and a reduction of hardware cost. For a input signal, a white Gaussian noise and a real speech signal with a environment noises are used for a performance estimation of the proposed algorithm. As a result of computer simulation, the proposed AEC has a low asymptotic error, a low computation complexity and a robust performance.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.15 no.9
• /
• pp.3138-3150
• /
• 2021

Multimedia services on the Internet are continuously increasing. Accordingly, the demand for a technology for efficiently delivering multimedia traffic is also constantly increasing. The multicast technique, that delivers the same content to several destinations, is constantly being developed. This technique delivers a content from a source to all destinations through the multicast tree. The multicast tree with low cost increases the utilization of network resources. However, the finding of the optimal multicast tree that has the minimum link costs is very difficult and its calculation complexity is the same as the complexity of the Steiner tree calculation which is NP-complete. Therefore, we need an effective way to obtain a multicast tree with low cost and less calculation time on SDN-based smart network platforms. In this paper, we propose a new multicast tree generation algorithm which produces a multicast tree using an agent trained by model-based meta reinforcement learning. Experiments verified that the proposed algorithm generated multicast trees in less time compared with existing approximation algorithms. It produced multicast trees with low cost in a dynamic network environment compared with the previous DQN-based algorithm.

• Proceedings of the IEEK Conference
• /
• 1998.10a
• /
• pp.1183-1186
• /
• 1998

Adaptive nois canceller can extract the noiseremoved spech in noisy speech signal by adapting the filter-coefficients to the background noise environment. A kind of LMS algorithm is one of the most popular adaptive algorithm for noise cancellation due to low complexity, good numerical property and the merit of easy implementation. However there is the matter of increasing misadjustment at voiced speech signal. Therefore the demanded speech signal may be extracted. In this paper, we propose a fast and noise robust wavelet packet adaptive noise canceller with NLMS-SUM method LMS combined algorithm. That is, we decompose the frequency of noisy speech signal at the base of the proposed analysis tree structure. NLMS algorithm in low frequency band can efficiently dliminate the effect of the low frequency noise and SUM method LMS algorithm at each high frequency band can remove the high frequency nosie. The proposed wavelet packet adaptive noise canceller is enhanced the more in SNR and according to Itakura-Satio(IS) distance, it is closer to the clean speech signal than any other previous adaptive noise canceller.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.31 no.2A
• /
• pp.176-186
• /
• 2006

In this paper, we propose an enhanced symbol detector algorithm for 2.45GHz LR-WPAN(Low-Rate Wireless Personal Area Network) receiver. Because the frequency offset of $\pm$80ppm on 2.45GHz band is recommended in IEEE 802.15.4 LR-WPAN(Low-Rate Wireless Personal Area Network) specification, a symbol detector algorithm having stable operation in the channel environment with large frequency offset is required. For robustness to the frequency offset, non-coherent detection-based symbol detector algorithm is typically applied in the LR-WPAN receiver modem. However, the noncoherent symbol detector has increased performance degradation and hardware complexity due to squaring loss of I/Q squaring operation. Therefore we propose a coherent detection-based symbol detector algorithm with frequency offset compensation using a preamble symbol. The proposed algorithm is more suitable for LR-WPAN receiver aimed at low-cost, low-power and low-complexity than the non-coherent symbol detector, since it can reduce performance degradation due to squaring loss of I/Q squaring operation and implementation complexity. Simulation results show that the proposed algorithm has performance improvement of about 1dB in various channel environments.

• Journal of information and communication convergence engineering
• /
• v.15 no.1
• /
• pp.7-13
• /
• 2017

We consider a distributed estimation where many nodes remotely placed at known locations collect the measurements of the parameter of interest, quantize these measurements, and transmit the quantized data to a fusion node; this fusion node performs the parameter estimation. Noting that quantizers at nodes should operate in a non-regular framework where multiple codewords or quantization partitions can be mapped from a single measurement to improve the system performance, we propose a low-weight estimation algorithm that finds the most feasible combination of codewords. This combination is found by computing the weighted sum of the possible combinations whose weights are obtained by counting their occurrence in a learning process. Otherwise, tremendous complexity will be inevitable due to multiple codewords or partitions interpreted from non-regular quantized data. We conduct extensive experiments to demonstrate that the proposed algorithm provides a statistically significant performance gain with low complexity as compared to typical estimation techniques.

• Proceedings of the IEEK Conference
• /
• 2002.07a
• /
• pp.317-320
• /
• 2002

In this paper, we will present the design and implementation of the KASUMI crypto algorithm and confidentiality algorithm (f8) to an hardware chip for 3GPP system. The f8 algorithm is based on the KASUMI which is a block cipher that produces a 64-bit output from a 64-bit input under the control of a 128-bit key. Various architectures (low hardware complexity version and high performance version) of the KASUMI are made with a Xilinx FPGA and the characteristics such as hardware complexity and thor performance are analyzed.

• International Journal of Internet, Broadcasting and Communication
• /
• v.9 no.1
• /
• pp.72-80
• /
• 2017

In this work, an efficient transmit antenna selection approach for the quadrature spatial modulation (QSM) systems is proposed. The conventional Euclidean distance antenna selection (EDAS)-based schemes in QSM have too high computational complexity for practical use. The proposed antenna selection algorithm is based on approximation of the EDAS decision metric employed for QSM. The elimination of imaginary parts in the decision metric enables decoupling of the approximated decision metric, which enormously reduces the complexity. The proposed method is also evaluated via simulations in terms of symbol error rate (SER) performance and compared with the conventional EDAS methods in QSM systems.