• Journal of the Korean Institute of Telematics and Electronics B
• /
• v.30B no.12
• /
• pp.59-66
• /
• 1993

In this paper we propose an adaptive update rate tracking algorithm for a phased array radar, based on the interacting multiple model(IMM) algorithm. The purpose of the IMM algorithm hers is twofold: 1) to estimate and predict the target states, and 2) to estimate the level of the process noise. Using the estimate of the process noise level adapted to target dynamics, the update interval is determined to maintain a desired prediction accuracy so that the radar system load is minimized. The adaptive update rate tracking algorithm is implemented for a phased array radar and evaluated with Monte Carlo simulations on various trajectories. The evaluation results of the proposed algorithm and a standard Kalman filter without the adaptive update rate control are presented to compare.

• Journal of the Korean Institute of Telematics and Electronics B
• /
• v.31B no.3
• /
• pp.39-46
• /
• 1994

In this paper, three types of parameter update law which can be used in model reference adaptive control are suggested based on speed-gradient algorithm which was introduced by Fradkov. It is shown that the parameter update law which was proposed by Narendra is a special from of these laws and that proposed parameter update laws can insure the global stability under some conditions such as attainability and convexity. We also comment that the transfer function of reference model shoud be positive real for the realization of parameter update law.

• Proceedings of the KIEE Conference
• /
• 2003.11c
• /
• pp.689-692
• /
• 2003

In this paper, we propose an adaptive beamforming algorithm for array antenna. The proposed beamforming algorithm, based on Block LMS (Block - Least Mean Squares) algorithm, has a variable step size from coefficient update. This method shows some advantages that the convergence speed is fast and the calculation time can reduced using a block LMS algorithm from frequency domain. As the adaptive parameter approaches a stationary state, it could reduce the number of filter coefficient update with the help of various step size. In this paper we compared the efficiency of the proposed algorithm with a standard LMS algorithm which is a representative method of adaptive beamforming.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2002.05a
• /
• pp.509-513
• /
• 2002

This paper presents a semi-blind Minimum Mean Square Error (MMSE) beamforming adaptive algorithm used far OFDM/CDMA combined system. The proposed algorithm exploits the transmitting pilot signal in the initial period of the transmission to update the weight vector. Then it applies the blind adaptive period to update the weight vector, in which the pilot signal is no longer used. The derivation of the algorithm based on the Mean Square Error (MSE) criterion is also presented. Computer simulation is carried out to verify the performance of the proposed approach.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.11 no.5
• /
• pp.2723-2740
• /
• 2017

Steganographic schemes which are based on minimizing an additive distortion function defined the overall impacts after embedding as the sum of embedding costs for individual image element. However, mutual impacts during embedding are often ignored. In this paper, an adaptive JPEG steganographic method based on weight distribution for embedding costs is proposed. The method takes mutual impacts during embedding in consideration. Firstly, an analysis is made about the factors that affect embedding fluctuations among JPEG coefficients. Then the Distortion Update Strategy (DUS) of updating the distortion costs is proposed, enabling to dynamically update the embedding costs group by group. At last, a kind of adaptive JPEG steganographic algorithm is designed combining with the update strategy and well-known additive distortion function. The experimental result illustrates that the proposed algorithm gains a superior performance in the fight against the current state-of-the-art steganalyzers with high-dimensional features.

• Journal of the Korea Society of Computer and Information
• /
• v.21 no.4
• /
• pp.17-24
• /
• 2016

In this paper, we propose a AH LSU(Advanced Hybrid QoS Routing Link State Update) Algorithm that improves the performance of Hybrid LSU(Hybrid QoS Link State State Update) Algorithm with statistical information of flow holding time in network. AH LSU algorithm has had both advantages of LSU message control in periodic QoS routing LSU algorithm and QoS routing performance in adaptive LSU algorithm. It has the mechanism that calculate LSU message transmission priority using the flow of statistical request bandwidth and available bandwidth and include MLMR(Meaningless LSU Message Removal) mechanism. MLMR mechanism can remove the meaningless LSU message generating repeatedly in short time. We have evaluated the performance of the MLMR mechanism, the proposed algorithm and the existing algorithms on MCI simulation network. We use the performance metric as the QoS routing blocking rate and the mean update rate per link, it thus appears that we have verified the performance of this algorithm.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.28 no.11C
• /
• pp.1161-1168
• /
• 2003

In this paper, we propose an improved statistical model-based voice activity detection algorithm and threshold update method. We first improve signal-to-noise ratio by using speech enhancement preprocessing algorithm combined power subtraction method and matched filter, then apply it to LLR test optimum decision rule for improving the performance even in low SNR conditions. And we propose an adaptive threshold update method that was not concerned in any papers. We also perform extensive computer simulations to demonstrate the performance improvement of the proposed VAD algorithm employing the proposed speech enhancement preprocessing algorithm and adaptive threshold update method under various background noise environments. Finally we verify our results by comparing ITU-T G.729 Annex B.

• ETRI Journal
• /
• v.28 no.6
• /
• pp.815-818
• /
• 2006

In the global Internet, a constraint-based routing algorithm performs the function of selecting a routing path while satisfying some given constraints rather than selecting the shortest path based on physical topology. It is necessary for constraint-based routing to disseminate and update link state information. The triggering policy of link state updates significantly affects the volume of update traffic and the quality of services (QoS). In this letter, we propose an adaptive triggering policy based on link-usage statistics in order to reduce the volume of link state update traffic without deterioration of QoS. Also, we evaluate the performance of the proposed policy via simulations.

• Proceedings of the KIEE Conference
• /
• 2007.07a
• /
• pp.1730-1731
• /
• 2007

In this paper, we present a direct adaptive control method using neural networks for the control of nonlinear systems. The weights of neural networks are trained by an adaptive backpropagation algorithm based on Lyapunov stability theory. We develop the parameter update-laws using the neural network input and the error between the desired output and the output of nonlinear plant to update the weights of a neural network in the sense that Lyapunove stability theory. Beside the output tracking error is asymptotically converged to zero.

• Proceedings of the IEEK Conference
• /
• 1998.10a
• /
• pp.1187-1190
• /
• 1998

In this paper we propose a new efficient generalized sidelobe canceller(GSC) algorithm, using the efficient frequency domain LMS algorithm, which has much less weights to update. We only update part of all the weights according to magnitude of each frequency bin. So, the new proposed GSC algorithm, which is called censored GSC(C-GSC), can greatly reduce the computational complexity.