• Journal of the Korean Data and Information Science Society
• /
• v.25 no.5
• /
• pp.1079-1094
• /
• 2014

In this paper, we study efficient gene selection methods by using conditional mutual information. We suggest gene selection methods using conditional mutual information based on semiparametric methods utilizing multivariate normal distribution and Edgeworth approximation. We compare our suggested methods with other methods such as mutual information filter, SVM-RFE, Cai et al. (2009)'s gene selection (MIGS-original) in SVM classification. By these experiments, we show that gene selection methods using conditional mutual information based on semiparametric methods have better performance than mutual information filter. Furthermore, we show that they take far less computing time than Cai et al. (2009)'s gene selection but have similar performance.

• Journal of the Institute of Electronics Engineers of Korea SP
• /
• v.41 no.6
• /
• pp.271-278
• /
• 2004

In this paper, we propose a content-based audio genre classification algorithm that automatically classifies the query audio into five genres such as Classic, Hiphop, Jazz, Rock, Speech using digital sign processing approach. From the 20 seconds query audio file, the audio signal is segmented into 23ms frame with non-overlapped hamming window and 54 dimensional feature vectors, including Spectral Centroid, Rolloff, Flux, LPC, MFCC, is extracted from each query audio. For the classification algorithm, k-NN, Gaussian, GMM classifier is used. In order to choose optimum features from the 54 dimension feature vectors, SFS(Sequential Forward Selection) method is applied to draw 10 dimension optimum features and these are used for the genre classification algorithm. From the experimental result, we can verify the superior performance of the proposed method that provides near 90% success rate for the genre classification which means 10%∼20% improvements over the previous methods. For the case of actual user system environment, feature vector is extracted from the random interval of the query audio and it shows overall 80% success rate except extreme cases of beginning and ending portion of the query audio file.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.37 no.5B
• /
• pp.327-337
• /
• 2012

There have been lots of researches on the optimal relay selection in relay-based systems. However, most researches have been focused on the maximization of transmission capacity with a constraint of sum power at both transmitter and relays. In Ad-hoc networks where relays have batteries of limited power, it is imperative to minimize the energy consumption while maintaining the required quality-of-service (QoS). In this paper, we propose an optimal relay selection strategy to minimize the relay power consumption while satisfying the required signal-to-noise ratio (SNR). Through intensive simulations, we show the proposed method is more effective in terms of energy consumption and guarantee lower transmission failure probability in multi-hop Ad-hoc environments.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.36 no.5A
• /
• pp.511-520
• /
• 2011

In this paper, we introduce a multiuser (MU) scheduling method for multiuser amplify-and-forward relay systems, which selects both the transmission mode, i.e., either one- or two-hop transmission, and the desired user via two steps. A closed-form expression for the average achievable rate of the proposed scheduling is derived under two transmission modes with MU scheduling, and its asymptotic solution is also analyzed in the limit of large number of mobile stations. Based on the analysis, we perform our two-step scheduling algorithm: the transmission mode selection followed by the user selection that needs partial feedback for instantaneous signal-to-noise ratios (SNRs) to the base station. We also analyze the average SNR condition such that the MU diversity gain is fully exploited. In addition, it is examined how to further reduce a quantity of feedback under certain conditions. The proposed algorithm shows the comparable achievable rate to that of the optimal one using full feedback information, while its required feedback overhead is reduced below half of the optimal one.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
• /
• v.11 no.6
• /
• pp.638-644
• /
• 2018

Relay systems have recently gained attentions because of its capability of cell coverage extension and the power gain as the one of key technologies for 5G. Relays can be exploited for small-cell base stations and the autonomous network, where communication devices communicate with each other cooperatively. Therefore, the relay technology is expected to enable the low power and large capacity communication. In order to maximize the benefits of using a limited number of relays, the efficient relay selection method is required. Especially, when two nodes exchange their data with each other via relay, the relay selection can maximize the average data rate by the spatial location of the relay. For this purpose, the average data rate is analyzed first according to the relay selection. In this paper, we analyzed the average data rate when two nodes exchange their data via dual-hop decode and forward relaying considering the interference by the concurrent transmission under Nakagami-m fading channel. The correctness of the analysis is verified by the Monte Carlo simulation. The results show that the concurrent transmission is superior to the non-concurrent transmission in the high required data rate region rather than in the low required data rate region.

• Journal of Broadcast Engineering
• /
• v.14 no.1
• /
• pp.59-69
• /
• 2009

A bi-directional symmetric prediction technique has been developed to improve coding efficiency of B-slice and to reduce the computational complexity required to estimate two motion vectors. On the contrary to the conventional bi-directional mode which encodes both forward and backward motion vectors, it only encodes a single forward motion vector, and the missing backward motion vector is derived in a symmetric way from the forward motion vector using temporal distance between forward/backward reference frames to and from the current B picture. Since the backward motion vector is derived from the forward motion vector, it can halve the computational complexity for motion estimation, and also reduces motion vector data to encode. This technique always derives the backward motion vector from the forward motion vector, however, there are cases when the forward motion vector is better to be derived from the backward motion vector especially in scene changes. In this paper, we generalize the idea of the symmetric coding with forward motion vector coding, and propose a new symmetric coding with backward motion vector coding and adaptive selection between the conventional symmetric mode and the proposed symmetric mode based on rate-distortion optimization.

• Proceedings of the Korean Institute of Intelligent Systems Conference
• /
• 2007.11a
• /
• pp.11-14
• /
• 2007

인간과 컴퓨터간의 상호교류 하는데 있어서 감정 인식은 필수라 하겠다. 그래서 본 논문에서는 음성 신호 및 얼굴 영상을 BL(Bayesian Learning)과 PCA(Principal Component Analysis)에 적용하여 5가지 감정 (Normal, Happy, Sad, Anger, Surprise) 으로 패턴 분류하였다. 그리고 각각 신호의 단점을 보완하고 인식률을 높이기 위해 결정 융합 방법과 특징 융합 방법을 이용하여 감정융합을 실행하였다. 결정 융합 방법은 각각 인식 시스템을 통해 얻어진 인식 결과 값을 퍼지 소속 함수에 적용하여 감정 융합하였으며, 특정 융합 방법은 SFS(Sequential Forward Selection)특정 선택 방법을 통해 우수한 특정들을 선택한 후 MLP(Multi Layer Perceptron) 기반 신경망(Neural Networks)에 적용하여 감정 융합을 실행하였다.

• Journal of Korea Multimedia Society
• /
• v.10 no.11
• /
• pp.1530-1537
• /
• 2007

In this paper, we implemented a speech emotion recognition system that can distinguish human emotional states from recorded speech captured by a single microphone and classify them into four categories: neutrality, happiness, sadness and anger. In general, a speech recorded with a microphone contains background noises due to the speaker environment and the microphone characteristic, which can result in serious system performance degradation. In order to minimize the effect of these noises and to improve the system performance, a MA(Moving Average) filter with a relatively simple structure and low computational complexity was adopted. Then a SFS(Sequential Forward Selection) feature optimization method was implemented to further improve and stabilize the system performance. For speech emotion classification, a SVM pattern classifier is used. The experimental results indicate the emotional classification performance around 65% in the computer simulation and 62% on the ARM platform.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.14 no.1
• /
• pp.1-19
• /
• 2020

In an underlay cognitive simultaneous wireless information and power transfer (SWIPT) network, communication from secondary user (SU) to secondary destination (SD) is accomplished with decode-and-forward (DF) relays. Multiple energy-constrained relays are assumed to harvest energy from SU via power splitting (PS) protocol and complete SU secure information transmission with beamforming. Hence, physical layer security (PLS) is investigated in cognitive SWIPT network. In order to interfere with eavesdropper and improve relay's energy efficiency, a destination-assisted jamming scheme is proposed. Namely, SD transmits artificial noise (AN) to interfere with eavesdropping, while jamming signal can also provide harvested energy to relays. Beamforming vector and power splitting ratio are jointly optimized with the objective of SU secrecy capacity maximization. We solve this non-convex optimization problem via a general two-stage procedure. Firstly, we obtain the optimal beamforming vector through semi-definite relaxation (SDR) method with a fixed power splitting ratio. Secondly, the best power splitting ratio can be obtained by one-dimensional search. We provide simulation results to verify the proposed solution. Simulation results show that the scheme achieves the maximum SD secrecy rate with appropriate selection of power splitting ratio, and the proposed scheme guarantees security in cognitive SWIPT networks.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2015.10a
• /
• pp.105-106
• /
• 2015

본 논문에서는 DTN(Delay Tolerant Network) 환경에서 효율적인 메시지 전달을 위해 확률적으로 중계 노드를 선택하는 기법을 제안한다. DTN은 종단 간 연결이 불확실한 네트워크에서의 통신을 Store-Carry-Forward 방식을 사용하여 메시지를 목적 노드에 전달한다. 또한 종단 간 연결이 불확실한 상황에서도 중계 노드를 통해 메시지를 목적 노드에 전달하여 높은 전송률을 보장한다. 하지만 에피데믹(Epidemic) 라우팅이나 Spray and Wait 라우팅과 같은 기존 다중 복사 라우팅 알고리즘은 접촉한 모든 노드에게 메시지를 복사하여 메시지 복사로 인한 오버헤드가 높아진다. 반면에 PROPHET 라우팅과 같은 단일 복사 알고리즘은 적은 오버헤드를 발생시키지만 중계 노드 수 감소로 인한 메시지 전송률 감소 현상이 나타난다. 본 논문에서 제안하는 알고리즘은 기존 DTN 라우팅의 문제점을 보완하기 위해 확률적으로 노드 분포를 분석하여 현재 네트워크에 효율적인 메시지 복사 방식을 선택하여 작동한다. 본 논문에서는 제안하는 알고리즘이 기존 DTN 라우팅 알고리즘과 오버헤드와 전송률을 비교하여 더 효율적임을 증명한다.