• Proceedings of the KIEE Conference
• /
• 1999.07g
• /
• pp.3135-3137
• /
• 1999

We propose two robust blind equalization algorithms based on multi-stage clustering blind equalization algorithm, which are called a complex classification update algorithm(CCUA) and an error compensation algorithm(ECA). The first algorithm is a tap-updating algorithm which each computes classified real and imaginary parts in order to reduce computations and the complexity of implementation as a stage increase. The second one is a algorithm which can achieve faster convergence speed because error of equalizer input make always fixed. Test results confirm that the proposed algorithms with faster convergence and lower complexity outperforms both constant modulus algorithm (CMA) and conventional multi-stage blind clustering algorithm(MSA) in reducing the SER as well as the MSE at the equalizer output.

• Journal of the Korean Solar Energy Society
• /
• v.38 no.2
• /
• pp.1-13
• /
• 2018

This paper deals with the NREL (National Renewable Energy Laboratory) 5-MW reference wind turbine. The controller which include MPPT (Maximum power point tracking) control algorithm and tower load reduction control algorithm was designed by MATLAB Simulink. This paper propose a tower damper algorithm to improve the existing tower damper algorithm. To improve the existing tower damper algorithm, proposed tower damper algorithm were applied the thrust sensitivity scheduling and PI control method. The thrust sensitivity scheduling was calculated by thrust force formula which include thrust coefficient table. Power and Tower root moment DEL (Damage Equivalent Load) was set as a performance index to verify the load reduction algorithm. The simulation were performed 600 seconds under the wind conditions of the NTM (Normal Turbulence Model), TI (Turbulence Intensity)16% and 12~25m/s average wind speed. The effect of the proposed tower damper algorithm is confirmed through PSD (Power Spectral Density). The proposed tower damper algorithm reduces the fore-aft moment DEL of the tower up to 6% than the existing tower damper algorithm.

• Journal of KIISE:Software and Applications
• /
• v.28 no.9
• /
• pp.603-611
• /
• 2001

This paper proposes a novel fast layer-by-layer algorithm that has better generalization capability. In the proposed algorithm, the weights of the hidden layer are updated by the target vector of the hidden layer obtained by least squares method. The proposed algorithm improves the learning speed that can occur due to the small magnitude of the gradient vector in the hidden layer. This algorithm was tested in a handwritten digits recognition problem. The learning speed of the proposed algorithm was faster than those of error back propagation algorithm and modified error function algorithm, and similar to those of Ooyen's method and layer-by-layer algorithm. Moreover, the simulation results showed that the proposed algorithm had the best generalization capability among them regardless of the number of hidden nodes. The proposed algorithm has the advantages of the learning speed of layer-by-layer algorithm and the generalization capability of error back propagation algorithm and modified error function algorithm.

• Journal of the Institute of Electronics Engineers of Korea TC
• /
• v.46 no.11
• /
• pp.32-39
• /
• 2009

In this thesis, design effective elimination interference algorithm of ICS repeat system for repeater that improve frequency efficiency. Gennerally, LMS Algorithm apply to ICS repeat system. Error convergence speed and accuracy of LMS Algorithm are influenced by reference signal. For improve LMS Algorithm, suggest Adaptive searching channel estimate algorithm. For using channel characteristic, adaptive searching channel estimate algorithm make reference signal similar interference signal by convolution operation and complement LMS algorithm demerit. For make channel similar pratical channel, apply Jake's Rayleigh multi-path model. LMS algorithm and suggested adaptive searching channel estimate algorithm that have 16 taps apply to ICS repeat system under Rayleigh multi-path channel, so simulate with MATLAB. According to simulate, ICS repeat system with LMS algorithm show -40 dB mean square error convergent after 110 datas iteration and ICS repeat system with adaptive searching channel estimate algorithm show -80 dB mean square en-or convergent after 120 datas iteration. Analyze simulation result, suggested adaptive searching channel estimate algorithm show 40 dB accuracy than LMS algorithm.

• Journal of Computing Science and Engineering
• /
• v.8 no.1
• /
• pp.1-10
• /
• 2014

The Bacterial Foraging Optimization Algorithm is a swarm intelligence optimization algorithm. This paper first analyzes the chemotaxis, as well as elimination and dispersal operation, based on the basic Bacterial Foraging Optimization Algorithm. The elimination and dispersal operation makes a bacterium which has found or nearly found an optimal position escape away from that position, which greatly affects the convergence speed of the algorithm. In order to avoid this escape, the sphere of action of the elimination and dispersal operation can be altered in accordance with the generations of evolution. Secondly, we put forward an algorithm of an adaptive adjustment of step length we called improved bacterial foraging optimization (IBFO) after making a detailed analysis of the impacts of the step length on the efficiency and accuracy of the algorithm, based on chemotaxis operation. The classic test functions show that the convergence speed and accuracy of the IBFO algorithm is much better than the original algorithm.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.33 no.8A
• /
• pp.805-814
• /
• 2008

Both EPCglobal Generation-2 (Gen2) for passive RFID systems and Intelleflex for semi-passive RFID systems use probabilistic slotted ALOHA with Q algorithm, which is a kind of dynamic framed slotted ALOHA (DFSA), as the tag anti-collision algorithm. A better tag anti-collision algorithm can reduce collisions so as to increase the efficiency of tag identification. In this paper, we introduce and analyze the estimation methods of the number of slots and tags for DFSA. To increase the efficiency of tag identification, we propose two new tag anti-collision algorithms, which are Chebyshev's inequality (CHI) algorithm and hybrid Q algorithm, and compare them with the conventional Q algorithm and adaptive adjustable framed Q (AAFQ) algorithm, which is mentioned in Part I. The simulation results show that AAFQ performs the best in Gen2 scenario. However, in Intelleflex scenario the proposed hybrid Q algorithm is the best. That is, hybrid Q provides the minimum identification time, shows the more consistent collision ratio, and maximizes throughput and system efficiency in Intelleflex scenario.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.29 no.8A
• /
• pp.942-949
• /
• 2004

This paper proposes and analyzes the anti-collision algorithm in Ubiquitous ID system. We mathematically compares the performance of the proposed algorithm with that of binary search algorithm, slotted binary tree algorithm using time slot, and bit-by-bit binary tree algorithm proposed by Auto-ID center. We also validated analytic results using OPNET simulation. Based on the analytic results, comparing the proposed algorithm with bit-by-bit algorithm which is the best of existing algorithms, the performance of proposed algorithm is about 5% higher when the number of tags is 20, and 100% higher when the number of tags is 200.

• Journal of the Institute of Electronics Engineers of Korea TC
• /
• v.42 no.5 s.335
• /
• pp.47-54
• /
• 2005

This paper proposes and analyzes a Tag Anti-collision algorithm in RFID system. We mathematically compare the performance of the proposed algorithm with existing binary algorithms(binary search algorithm, slotted binary tree algorithm using time slot, and bit-by-bit binary tree algorithm proposed by Auto-ID center). We also validated analytic results using OPNET simulation. Based on analytic result, comparing the proposed Improved bit-by-bit binary tree algerian with bit-by-bit binary tree algorithm which is the best of existing algorithms, the performance of Improved bit-by-bit binary tree algorithm is about $304\%$ higher when the number of tags is 20, and $839\%$ higher when the number of tags is 200.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
• /
• 2007.11a
• /
• pp.737-742
• /
• 2007

The method of the reducing duct noise can be classified by passive and active control techniques. However, passive control has a limited effect of noise reduction at low frequencies (below 500Hz) and is limited by the space. On the other hand, active control can overcome these passive control limitations. The active control technique mostly uses the Least-Mean-Square (LMS) algorithm, because the LMS algorithm can easily obtain the complex transfer function in real-time particularly when the Filtered-X LMS (FXLMS) algorithm is applied to an active noise control (ANC) system. However, the convergence performance of the LMS algorithm decreases slightly so it may delay the convergence time when the FXLMS algorithm is applied to the active control of duct noise. Thus the Co-FXLMS algorithm was developed to improve the control performance in order to solve this problem. The Co-FXLMS algorithm is realized by using an estimate of the cross correlation between the adaptation error and the filtered input signal to control the step size. In this paper, the performance of the Co-FXLMS algorithm is presented in comparison with the FXLMS algorithm. Simulation results show that active noise control using Co-FXLMS is effective in reducing duct noise.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.12 no.7
• /
• pp.3455-3474
• /
• 2018

As a unique form of signed-digit representation, non-adjacent form (NAF) minimizes Hamming weight by removing a stream of non-zero bits from the binary representation of positive integer. Thanks to this strong point, NAF has been used in various applications such as cryptography, packet filtering and so on. In this paper, to improve the NAF conversion speed of the $NAF_w$ algorithm, we propose a new NAF conversion algorithm, called w-bit Shifting Non-Adjacent Form($SNAF_w$), where w is width of scanning window. By skipping some unnecessary bit comparisons, the proposed algorithm improves the NAF conversion speed of the $NAF_w$ algorithm. To verify the excellence of the $SNAF_w$ algorithm, the $NAF_w$ algorithm and the $SNAF_w$ algorithm are implemented in the 8-bit microprocessor ATmega128. By measuring CPU cycle counter for the NAF conversion under various input patterns, we show that the $SNAF_2$ algorithm not only increases the NAF conversion speed by 24% on average but also reduces deviation in the NAF conversion time for each input pattern by 36%, compared to the $NAF_2$ algorithm. In addition, we show that $SNAF_w$ algorithm is always faster than $NAF_w$ algorithm, regardless of the size of w.