• ETRI Journal
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• v.29 no.5
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• pp.596-606
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• 2007

It is well known that an OFDM receiver is vulnerable to synchronization errors. Despite fine estimations used in the initial acquisition, there are still residual synchronization errors. Though these errors are very small, they severely degrade the bit error rate (BER) performance. In this paper, we propose a residual error elimination scheme for the digital OFDM baseband receiver aiming to improve the overall BER performance. Three improvements on existing schemes are made: a pilot-aided recursive algorithm for joint estimation of the residual carrier frequency and sampling time offsets; a delay-based timing error correction technique, which smoothly adjusts the incoming data stream without resampling disturbance; and a decision-directed channel gain update algorithm based on recursive least-squares criterion, which offers faster convergence and smaller error than the least-mean-squares algorithms. Simulation results show that the proposed scheme works well in the multipath channel, and its performance is close to that of an OFDM system with perfect synchronization parameters.

• The KIPS Transactions:PartD
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• v.9D no.4
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• pp.587-602
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• 2002

Replicated database system was emerged to resolve the problem of reduction of the availability and the reliability due to the communication failures and site errors generated at centralized database system. But if update transactions are many occurred, the update is equally executed for all replicated data. Therefore, there are many problems the same thing a message overhead generated by synchronization and the reduce of concurrency happened because of delaying the transaction. In this paper, I propose a new concurrency control algorithm for enhancing the degree of parallelism of the transaction in fully replicated database designed to improve the availability and the reliability. To improve the system performance in the replicated database should be performed the last operations in the submitted site of transactions and be independently executed update-only transactions composed of write-only transactions in all sites. I propose concurrency control method to maintain the consistency of the replicated database and reflect the result of update-only transactions in all sites. The superiority of the proposed method has been tested from the respondence and withdrawal rate. The results confirm the superiority of the proposed technique over classical correlation based method.

• Proceedings of the IEEK Conference
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• 2003.07d
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• pp.1239-1242
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• 2003

The neural networks are a famous model to learn the nonlinear function or nonlinear system. The main point of neural network is that the difference actual output from desired output is used to update weights. Usually, the gradient descent method is used for the learning process. On training process, if learning rate is too large, neural networks hardly guarantee convergence of neural networks. On the other hand, if learning rate is too small, the training spends much time. Therefore, one major problem in use of neural networks are to decrease the teaming time while neural networks are guaranteed convergence. In this paper, we suggest the model of fuzzy logic to neural networks to calibrate learning rate. This method is to tune learning rate dynamically according to error and demonstrates the optimization of training.

• Journal of Korean Society for Quality Management
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• v.30 no.4
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• pp.68-77
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• 2002

EM algorithm has good convergence rate for numerical procedures which converges on very small step. In the case of proportion estimation in a mixed distribution which has very big incomplete data or of update of new data continuously, however, EM algorithm highly depends on a initial value with slow convergence ratio. There have been many studies to improve the convergence rate of EM algorithm in estimating the proportion parameter of a mixed data. Among them, dynamic EM algorithm by Hurray Jorgensen and Titterington algorithm by D. M. Titterington are proven to have better convergence rate than the standard EM algorithm, when a new data is continuously updated. In this paper we suggest dynamic EM algorithm and Titterington algorithm for the estimation of a mixed Poisson distribution and compare them in terms of convergence rate by using a simulation method.

• Journal of KIISE:Computer Systems and Theory
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• v.33 no.3
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• pp.193-204
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• 2006

In most existing distributed Web systems, incoming requests are distributed to servers via Domain Name System (DNS). Although such systems are simple to implement, the address caching mechanism easily results in load unbalancing among servers. Moreover, modification of the DNS is necessary to load considering the server's state. In this paper, we propose a new dynamic load balancing method using dynamic DNS update and round-robin mechanism. The proposed method performs effective load balancing without modification of the DNS. In this method, a server can dynamically be added to or removed from the DNS list according to the server's load. By removing the overloaded server from the DNS list, the response time becomes faster. For dynamic scheduling, we propose a scheduling algorithm that considers the CPU, memory, and network usage. We can select a scheduling policy based on resources usage. The proposed system can easily be managed by a GUI-based management tool. Experiments show that modules implemented in this paper have low impact on the proposed system. Furthermore, experiments show that both the response time and the file transfer rate of the proposed system are faster than those of a pure Round-Robin DNS.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.33 no.9B
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• pp.832-844
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• 2008

Distributed localization algorithms are necessary for large-scale wireless sensor network applications. In this paper, we introduce an efficient node distribution based localization algorithm that emphasizes simple refinement and low system load for low-cost and low-rate wireless sensors. Each node adaptively chooses neighbor nodes for sensors, update its position estimate by minimizing a local cost function and then passes this update to the neighbor nodes. The update process considers a distribution of nodes for large-scale networks which have same density in a unit area for optimizing the system performance. Neighbor nodes are selected within a range which provides the smallest received signal strength error based on the real experiments. MATLAB simulation showed that the proposed algorithm is more accurate than trilateration and les complex than multidimensional scaling. The implementation on MicaZ using TinyOS-2.x confirmed the practicality of the proposed algorithm.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.40 no.5
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• pp.791-798
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• 2015

It has been grown interests of the convergence technologies about communication systems and vehicular industry. Vehicular communications enable a number of infotainment applications to serve cars under high mobility environments. To achieve this goal, a robust and accurate channel estimation scheme is of great importance. This paper proposes an enhanced Decision-Directed channel estimation scheme called PTAU(Pilot Tone Aided Update) for IEEE 802.11p in vehicular communication environment. Existing approaches which use subsequent data symbols to estimate channel response in time domain will lead to the error propagation. In this paper, we use the pilot subcarriers to get initial channel response, then utilize the correlation characteristics to update channel response in frequency domain. Finally, Analysis and simulation results reveal that the proposed scheme outperforms in bit error rate(BER), significantly improve the performance of the estimation.

• Journal of Broadcast Engineering
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• v.27 no.4
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• pp.561-568
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• 2022

Most deep learning-based video object segmentation methods perform the segmentation with past prediction information stored in external memory. In general, the more past information is stored in the memory, the better results can be obtained by accumulating evidence for various changes in the objects of interest. However, all information cannot be stored in the memory due to hardware limitations, resulting in performance degradation. In this paper, we propose a method of storing new information in the external memory without additional memory allocation. Specifically, after calculating the attention score between the existing memory and the information to be newly stored, new information is added to the corresponding memory according to each score. In this way, the method works robustly because the attention mechanism reflects the object changes well without using additional memory. In addition, the update rate is adaptively determined according to the accumulated number of matches in the memory so that the frequently updated samples store more information to maintain reliable information.

• Journal of Communications and Networks
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• v.10 no.1
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• pp.38-43
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• 2008

In this paper, adaptive channel borrowing approach fuzzy neural networks for load balancing (ACB-FNN) is presented to maximized the number of served calls and the depending on asymmetries traffic load problem. In a wireless network, the call's arrival rate, the call duration and the communication overhead between the base station and the mobile switch center are vague and uncertain. A new load balancing algorithm with cell involved negotiation is also presented in this paper. The ACB-FNN exhibits better learning abilities, optimization abilities, robustness, and fault-tolerant capability thus yielding better performance compared with other algorithms. It aims to efficiently satisfy their diverse quality-of-service (QoS) requirements. The results show that our algorithm has lower blocking rate, lower dropping rate, less update overhead, and shorter channel acquisition delay than previous methods.

• Proceedings of the KIEE Conference
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• 1994.07b
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• pp.1435-1438
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• 1994

The effects of Ge composition variation in $a-Si_{1-x}Ge_x:H$ alloy p-i-n solar cells on the physical properties and current density-voltage characteristics are analyzed by a new simulation modelling based on the update published experimental datas. The simulation modelling includes newly formulated density of gap density spectrum corresponding to Ge composition variation and utilizes the newly derived generation rate formulars which include the reflection coefficients and can apply to multijunction structures as well as single junction structure. The effects in $a-Si_{1-x}Ge_x:H$ single junction are analyzed through the efficiency, fill factor, open circuit voltage, short circuit current density, free carriers, trap carriers, electric field, generation rate and recombination rate. Based on the results analyzed in single junction structure, the applications to multiple junction structures are discussed and the optimal conditions reaching to a high performance are investigated.