• Journal of the Korea Society of Computer and Information
• /
• v.26 no.2
• /
• pp.61-68
• /
• 2021

Recently, various technologies that use machine learning to classify malicious code have been studied. In order to enhance the effectiveness of machine learning, it is most important to extract properties to identify malicious codes and normal binaries. In this paper, we propose a feature extraction method for use in machine learning using recursive methods. The proposed method selects the final feature using recursive methods for individual features to maximize the performance of machine learning. In detail, we use the method of extracting the best performing features among individual feature at each stage, and then combining the extracted features. We extract features with the proposed method and apply them to machine learning algorithms such as Decision Tree, SVM, Random Forest, and KNN, to validate that machine learning performance improves as the steps continue.

• The Journal of the Acoustical Society of Korea
• /
• v.27 no.5
• /
• pp.256-261
• /
• 2008

In this paper, we propose a novel approach to improve the performance of minima controlled recursive averaging (MCRA) which is based on the conditional maximum a posteriori criterion. A crucial component of a practical speech enhancement system is the estimation of the noise power spectrum. One state-of-the-art approach is the minima controlled recursive averaging (MCRA) technique. The noise estimate in the MCRA technique is obtained by averaging past spectral power values based on a smoothing parameter that is adjusted by the signal presence probability in frequency subbands. We improve the MCRA using the speech presence probability which is the a posteriori probability conditioned on both the current observation the speech presence or absence of the previous frame. With the performance criteria of the ITU-T P.862 perceptual evaluation of speech quality (PESQ) and subjective evaluation of speech quality, we show that the proposed algorithm yields better results compared to the conventional MCRA-based scheme.

• International Journal of Control, Automation, and Systems
• /
• v.4 no.6
• /
• pp.736-747
• /
• 2006

Simultaneous Localization and Map Building(SLAM) is one of the fundamental problems in robot navigation. The Extended Kalman Filter(EKF), which is widely adopted in SLAM approaches, requires extensive computation. The conventional particle filter also needs intense computation to cover a high dimensional state space with particles. This paper proposes an efficient SLAM method based on the recursive unscented Kalman filtering in an environment including a large number of landmarks. The posterior probability distributions of the robot pose and the landmark locations are represented by their marginal Gaussian probability distributions. In particular, the posterior probability distribution of the robot pose is calculated recursively. Each landmark location is updated with the recursively updated robot pose. The proposed method reduces filtering dimensions and computational complexity significantly, and has produced very encouraging results for navigation experiments with noisy multiple simultaneous observations.

• Proceedings of the Korean Information Science Society Conference
• /
• 2005.11a
• /
• pp.922-924
• /
• 2005

실시간 시스템의 개발 및 운영에 사용되는 실시간 운영체제는 여러 개의 태스크가 동시에 작업할 수 있는 멀티태스킹 환경과 각 태스크에 우선순위를 부여하여 가장 높은 우선순위의 태스크가 CPU 를 선점하는 스케줄링 방법, 그리고 태스크간 동기화 및 통신을 위한 메커니즘을 제공하고 있다. 또한 여러 태스크들에 의해 사용되는 공유자원을 관리하기 위해 세마포어(Semaphore)를 사용하여 태스크간 동기화를 제공한다. 그러나 하나의 태스크가 세마포어를 이용하여 공유자원에 대해 여러 번 접근 할 경우, 데드락(Deadlock)을 일으킬 소지가 많다. 본 논문에서는 실시간 운영체제인 $iRTOS^{TM}$ 에서 데드락을 방지하기 위한 재귀적 세마포어(Recursive Semaphore)를 설계 및 구현하였다.

• ETRI Journal
• /
• v.25 no.2
• /
• pp.144-147
• /
• 2003

We propose a new serial concatenation scheme for space-time and recursive convolutional codes, in which a space-time code is used as the outer code and a single recursive convolutional code as the inner code. We discuss previously proposed serial concatenation schemes employing multiple inner codes and compare them with the new one. The proposed method and the previous one with joint decoding, both performing a combined decoding of the simultaneous output signals from multiple antennas, give a large performance gain over the separate decoding method. In decoding complexity, the new concatenation scheme has a lower complexity compared with the multiple encoding/joint decoding scheme due to the use of the single inner code. Simulation results for a communication system with two transmit and one receive antennas in a quasi-static Rayleigh fading channel show that the proposed scheme outperforms the previous schemes.

• Journal of the Korean Institute of Telematics and Electronics B
• /
• v.31B no.7
• /
• pp.33-41
• /
• 1994

A single channel adaptive noise canceling (ANC) technique with a recursive time delay estimator (RTDE) is presented for removing effects of additive noise on the speech signal. While the conventional method makes a reference signal for the adaptive filter using the pitch estimated on a frame basis from the input speech, the proposed method makes the reference signal using the delay estimated recursively on a sample-by-sample basis. As the RTDEs, the recursion formulae of autocorrelation function (ACF) and average magnitude difference function (AMDF) are derived. The normalized least mean square (NLMS) and recursive least square (RLS) algorithms are applied for adaptation of filter coefficients. Experimental results with noisy speech demonstrate that the proposed method improves the perceived speech quality as well as the signal-to-noise ratio and cepstral distance when compared with the conventional method.

• The Transactions of the Korean Institute of Electrical Engineers B
• /
• v.48 no.3
• /
• pp.139-143
• /
• 1999

This paper is on realization of the speed-sensorless vector control of an induction motor using the RLS(Recursive Least Square) algorithm. The speed estimator is including the RLS algorithm and a rotor flux observer. The RLS algorithm has speed and rotor time constant as parameter vectors and rotor flux observer is designed to have robustness to stator resistance variation and through the IP(Integral and Proportional) speed controller stable performance is obtained for estimating rotor speed. Finally the total algorithm are realized in induction motor drive system and its effectiveness is verified.

• Proceedings of the KSPS conference
• /
• 2002.11a
• /
• pp.179-182
• /
• 2002

The development of noise robust speech processing systems is becoming increasingly important as speech technology is currently widely applied in real world applications. Recently, to resolve such a noise problem, adaptive noise canceller(ANC) is frequently used, which is based upon adaptive filters. The adaptive recursive filters perform better than adaptive non-recursive filters due to the added poles, but the stability may be severely threatened. But these problems of adaptive recursive filters was solved by ACHARF algorithm. This paper presents a method which combines speaker verification system with ANC(Adaptive Noise Canceller) using the ACHARF algorithm. In the front-end stage, ANC is adopted to suppress the additive noise imposed on the speech signal. The results show that the performance of speaker verification system becomes better than before.

• Journal of Institute of Control, Robotics and Systems
• /
• v.6 no.12
• /
• pp.1053-1060
• /
• 2000

In this paper, a discrete-time variable structure control method using recursively defined switching function and a decoupled variable structure disturbance compensator is used to achieve high performance circular motion control of a CNC machining center. The discrete-time variable structure control with the decoupled disturbance compensator method developed in this paper uses a recursive switching function defined as the sum of the current tracking error vector and the previous value of the switching function multiplied by a positive constant less than one. This recursive switching function provides much improved performance compared to the method that uses a switching function defined only as a linear combination of the current tracking error. Enhancements in tracking performance are demonstrated in the circular motion control using a CNC milling machine.

• Proceedings of the KIEE Conference
• /
• 2011.07a
• /
• pp.1740-1741
• /
• 2011

This paper proposes a new linear recursive target state estimator for automotive collision warning system. The target motion is modeled in Cartesian coordinate system while the radar measurements such as range, line-of-sight angle and range rate are obtained in polar coordinate system. To solve the problem by nonlinear relation between these two coordinate system, a practical linear filter design scheme employing the predicted line-of-sight Cartesian coordinate system (PLCCS) is proposed. Especially, PLCCS can effectively incorporate range rate measurements into target tracking system. It is known that the utilization of range rate measurements enables the improvement of target tracking performance. Moreover, PLCCS based target tracking system is implemented by linear recursive filter structure and hence is more suitable scheme for the development of reliable collision warning system. The performance of the proposed method is demonstrated by computer simulations.