• Journal of the Institute of Electronics Engineers of Korea CI
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• v.42 no.1
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• pp.9-26
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• 2005

In the pursuit of ever higher levels of performance, recent computer systems have made use of deep pipeline, dynamic scheduling and multi-issue superscalar processor technologies. In this situations, branch prediction schemes are an essential part of modem microarchitectures because the penalty for a branch misprediction increases as pipelines deepen and the number of instructions issued per cycle increases. In this paper, we propose a novel branch prediction scheme, direction-gshare(d-gshare), to improve the prediction accuracy. At first, we model a neural network with the components that possibly affect the branch prediction accuracy, and analyze the variation of their weights based on the neural network information. Then, we newly add the component that has a high weight value to an original gshare scheme. We simulate our branch prediction scheme using Simple Scalar, a powerful event-driven simulator, and analyze the simulation results. Our results show that, compared to bimodal, two-level adaptive and gshare predictor, direction-gshare predictor(d-gshare. 3) outperforms, without additional hardware costs, by up to 4.1% and 1.5% in average for the default mont of embedded direction, and 11.8% in maximum and 3.7% in average for the optimal one.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.42 no.3 s.303
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• pp.73-80
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• 2005

Recently there have been many efforts to support searching and browsing based on the visual content of image and multimedia data. Most existing approaches to content-based image retrieval rely on query by example or user based low-level features such as color, shape, texture. But these methods of query are not easy to use and restrict. In this paper we propose a method for automatic color object extraction and labelling to support multiple queries of content-based image retrieval system. These approaches simplify the regions within images using single colorizing algorithm and extract color object using proposed Color and Spatial based Binary tree map(CSB tree map). And by searching over a large of number of processed regions, a index for the database is created by using proposed labelling method. This allows very fast indexing of the image by color contents of the images and spatial attributes. Futhermore, information about the labelled regions, such as the color set, size, and location, enables variable multiple queries that combine both color content and spatial relationships of regions. We proved our proposed system to be high performance through experiment comparable with another algorithm using 'Washington' image database.

• The Journal of the Acoustical Society of Korea
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• v.22 no.2
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• pp.121-128
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• 2003

Acoustic Echo Cancellation(m) is very active research topic having many applications like teleconference and hands-free communication and it employs Double Talk Detector(DTD) to indicate whether the near-end speaker is active or not. However. the DTD is very sensitive to the variation of acoustical environment and it sometimes provides wrong information about the near-end speaker. In this paper, we are focusing on the development of robust DTD algorithm which is a basic building block for reliable AEC system. The proposed AEC system consists of delayless subband AEC and narrow-band DTD. Delayless subband AEC has proven to have excellent performance of echo cancellation with a low complexity and high convergence speed. In addition, it solves the signal delay problem in the existing subband AEC. On the other hand, the proposed narrowband DTD is operating on low frequency subband. It can take most advantages from the narrow subband such as a low computational complexity due to the down-sampling and the reliable DTD decision making procedure because of the low-frequency nature of the subband signal. From the simulation results of the proposed narrowband DTD and wideband DTD, we confirm that the proposed DTD outperforms the wideband DTD in a sense of removing possible false decision making about the near-end speaker activity.

• Structural Monitoring and Maintenance
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• v.2 no.1
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• pp.77-93
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• 2015

The idea of using measured dynamic characteristics for damage detection is attractive because it allows for a global evaluation of the structural health and condition. However, vibration-based damage detection for complex structures such as long-span cable-supported bridges still remains a challenge. As a suspension or cable-stayed bridge involves in general thousands of structural components, the conventional damage detection methods based on model updating and/or parameter identification might result in ill-conditioning and non-uniqueness in the solution of inverse problems. Alternatively, methods that utilize, to the utmost extent, information from forward problems and avoid direct solution to inverse problems would be more suitable for vibration-based damage detection of long-span cable-supported bridges. The auto-associative neural network (ANN) technique and the probabilistic neural network (PNN) technique, that both eschew inverse problems, have been proposed for identifying and locating damage in suspension and cable-stayed bridges. Without the help of a structural model, ANNs with appropriate configuration can be trained using only the measured modal frequencies from healthy structure under varying environmental conditions, and a new set of modal frequency data acquired from an unknown state of the structure is then fed into the trained ANNs for damage presence identification. With the help of a structural model, PNNs can be configured using the relative changes of modal frequencies before and after damage by assuming damage at different locations, and then the measured modal frequencies from the structure can be presented to locate the damage. However, such formulated ANNs and PNNs may still be incompetent to identify damage occurring at the deck members of a cable-supported bridge because of very low modal sensitivity to the damage. The present study endeavors to enhance the damage identification capability of ANNs and PNNs when being applied for identification of damage incurred at deck members. Effort is first made to construct combined modal parameters which are synthesized from measured modal frequencies and modal shape components to train ANNs for damage alarming. With the purpose of improving identification accuracy, effort is then made to configure PNNs for damage localization by adapting the smoothing parameter in the Bayesian classifier to different values for different pattern classes. The performance of the ANNs with their input being modal frequencies and the combined modal parameters respectively and the PNNs with constant and adaptive smoothing parameters respectively is evaluated through simulation studies of identifying damage inflicted on different deck members of the double-deck suspension Tsing Ma Bridge.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.41 no.6
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• pp.209-220
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• 2004

The main feature of H.264 standard against conventional video standards is the high coding efficiency and the network friendliness. In spite of these outstanding features, it is not easy to implement H.264 codec as a real-time system due to its high requirement of memory bandwidth and intensive computation. Although the variable block size motion compensation using multiple reference frames is one of the key coding tools to bring about its main performance gain, it demands substantial computational complexity due to SAD (Sum of Absolute Difference) calculation among all possible combinations of coding modes to find the best motion vector. For speedup of motion estimation process, therefore, this paper proposes fast algorithms for both integer-pel and fractional-pel motion search. Since many conventional fast integer-pel motion estimation algorithms are not suitable for H.264 having variable motion block sizes, we propose the motion field adaptive search using the hierarchical block structure based on the diamond search applicable to variable motion block sizes. Besides, we also propose fast fractional-pel motion search using small diamond search centered by predictive motion vector based on statistical characteristic of motion vector.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.19 no.9
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• pp.1028-1036
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• 2008

In the OFDM system, IQ imbalance problem happens at the RF front-end of transceiver, which degrades the BER(bit error rate) performance because it affects the constellation in the received signal. Also, phase noise is generated in the local oscillator of transceivers and it destroys the orthogonality between the subcarriers. Conventional PNS algorithm is effective for phase noise suppression, but it is not useful anymore when there are jointly IQ(In-phase and Quadrature) imbalance and phase noise. Therefore, in this paper, we analyze the effect of IQ imbalance and phase noise generated in the down-conversion of the receiver. Then, we estimate and compensate the IQ imbalance and phase noise at the same time. Compared with the conventional method that IQ imbalance after IFFT is estimated and compensated in front of FFT via the feedback, this proposed method extracts and compensates effect of IQ imbalance after FFT stage. In case IQ imbalance and phase noise exist at the same time, we can decrease complexity because it is needless to use elimination of IQ imbalance in time domain and training sequences and preambles. Also, this method shows that it reduces the ICI and CPE component using adaptive forgetting factor of MMSE after FFT.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.49 no.1
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• pp.39-45
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• 2012

In this paper, a distributed 2-hop routing algorithm is proposed. The main purpose of the proposed algorithm is to reduce the overall power consumption of each sensor node so that the lifetime of WSN(wireless sensor network) is prolonged. At the beginning of each round, the base station transmits a synchronization signal that contains information on the priority table that is used to decide whether each sensor node is elected as a cluster head or not. The priority table is constructed so that sensor nodes closer to half energy distance from the base station get the higher priority. 2-hop routing is done as follows. Cluster heads inside half energy distance from the base station communicate with the base station directly. Those outside half energy distance have to decide whether they choose 2-hop routing or 1-hop routing. To do this, each cluster head outside half energy distance calculates the energy consumption needed to communicate with the base station via 1-level cluster head or directly. If less energy is needed when passing through the 1-level cluster head, 2-hop routing is chosen and if not, 1-hop routing is chosen. After routing is done each sensor nodes start sensing data.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.45 no.4
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• pp.53-63
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• 2008

Reader collision may occur when neighboring RFID readers use the same channel at the same time. Especially when the readers are operated in dense mode, even though many channels are available, because of frequent reader collisions we can not guarantee the performance of RFID readers. Conventional solutions such as FH(Frequency Hopping) or LBT(Listen Before Talk) are not effective in this situation because they can not schedule RFID readers effectively when RFID readers are operated in multi-channel, dense reader mode, In this paper, we propose a new RFID reader anti-collision algorithm which employs LBT, random backoff before channel access, and probabilistic channel hopping at the same time. While LBT and Random backoff before channel access reduces collisions between competing readers, probabilistic channel hopping increases channel utilization by adaptively changing the hopping probability by reflecting the reader density and utilization. Simulation results shows that our algorithm outperforms conventional methods.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.17 no.8 s.111
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• pp.773-787
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• 2006

An airborne radar is an essential aviation electronic system for the aircraft to perform various civil and/or military missions in all weather environments. This paper presents the design, development, and test results of the multi-mode X-band pulsed Doppler radar system test model for helicopter-borne flight test. This radar system consists of 4 LRUs(Line-Replacement Unit), which include antenna unit, transmitter and receiver unit, radar signal & data processing unit and display Unit. The developed core technologies include the planar array antenna, TWTA transmitter, coherent I/Q detector, digital pulse compression, MTI, DSP based Doppler FFT filter, adaptive CFAR, moving clutter compensation, platform motion stabilizer, and tracking capability. The design performance of the developed radar system is verified through various ground fixed and moving vehicle test as well as helicopter-borne field tests including MTD(Moving Target Detector) capability for the Doppler compensation due to the moving platform motion.

• Journal of the Institute of Electronics and Information Engineers
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• v.53 no.4
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• pp.142-148
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• 2016

Recently, human identification using various biological signals has been studied and human identification based on the gait has been actively studied. In this paper, we propose a human identification based on the EMG(Electromyography) signal of the thigh muscles that are used when walking. Various features such as RMS, MAV, VAR, WAMP, ZC, SSC, IEMG, MMAV1, MMAV2, MAVSLP, SSI, WL are extracted from EMG signal data and ANN(Artificial Neural Network) classifier is used for human identification. When we evaluated the recognition ratio per channel and features to select approptiate channels and features for human identification. The experimental results show that the rectus femoris, semitendinous, vastus lateralis are appropriate muscles for human identification and MAV, ZC, IEMG, MMAV1, MAVSLP are adaptable features for human identification. Experimental results also show that the average recognition ratio of method of using all channels and features is 99.7% and that of using selected 3 channels and 5 features is 96%. Therefore, we confirm that the EMG signal can be applied to gait based human identification and EMG signal based human identification using small number of adaptive muscles and features shows good performance.