• ETRI Journal
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• v.35 no.6
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• pp.1029-1037
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• 2013

This paper introduces a novel and fast synthesizing method for 3D motions of quadrupedal animals that uses only a small set of motion capture data. Unlike human motions, animal motions are relatively difficult to capture. Also, it is a challenge to synthesize continuously changing animal motions in real time because animals have various gait types according to their speed. The algorithm proposed herein, however, is able to synthesize continuously varying motions with proper limb configuration by using only one single cyclic animal motion per gait type based on the biologically driven Froude number. During the synthesis process, each gait type is automatically determined by its speed parameter, and the transition motions, which have not been entered as input, are synthesized accordingly by the optimized asynchronous motion blending technique. At the start time, given the user's control input, the motion path and spinal joints for turning are adjusted first and then the motion is stitched at any speed with proper transition motions to synthesize a long stream of motions.

• Journal of information and communication convergence engineering
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• v.8 no.3
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• pp.267-272
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• 2010

For the last decade, recurrent neural networks (RNNs) have been commonly applied to communications channel equalization. The major problems of gradient-based learning techniques, employed to train recurrent neural networks are slow convergence rates and long training sequences. In high-speed communications system, short training symbols and fast convergence speed are essentially required. In this paper, the derivative-free Kalman filter, so called the unscented Kalman filter (UKF), for training a fully connected RNN is presented in a state-space formulation of the system. The main features of the proposed recurrent neural equalizer are fast convergence speed and good performance using relatively short training symbols without the derivative computation. Through experiments of nonlinear channel equalization, the performance of the RNN with a derivative-free Kalman filter is evaluated.

• Journal of information and communication convergence engineering
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• v.8 no.5
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• pp.534-538
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• 2010

Efficient control of a marine engine requires an engine control unit (ECU) system that handles fast and precise signal processes for in-coming and out-going signals from fast running engines. In order to handle these roles, the sequential control has been adapted in the ECU system in small and medium size ship engines, which has caused high production cost and complexity of the system. Hence, this paper is focused on developing an distributed ECU system for high speed and high precision control of a marine engine by efficiently combining a CPLD chip and a microprocessor. By sharing load at the MCU with the designed CPLD chip, we could achieve in driving a marine engine with high speed and precise control so that the ECU board has been simplified and its production cost has been reduced.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.10
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• pp.199-203
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• 2013

In this paper, a fast algorithm of discrete cosine transform-based interpolation filter (DCT-IF) for HEVC (high efficiency video coding) encoder is proposed. DCT-IF filter accounts for around 30% of encoder complexity, according to the computational complexity analysis with the HEVC reference software. In this work, the proposed DCT-IF is optimized by applying frame-level interpolation, SIMD optimization, and task-level parallelization via OpenMP on a developed C-based HEVC encoder. Performance analysis is conducted by measuring speed-up factor of the proposed optimization technique on the developed encoder. The results show that speed-up factors by frame-level interpolation, SIMD, and OpenMP are approximately 38-46, 3.6-4.4, and 3.0-3.7, respectively. In the end, we achieved the speed-up factor of 498.4 with the proposed fast algorithm.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.2 no.3
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• pp.135-149
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• 2008

Traditional attack detection schemes based on packets or flows have very high computational complexity. And, network based anomaly detection schemes can reduce the complexity, but they have a limitation to figure out the pattern of the distributed global scale network attack. In this paper, we propose an efficient and fast method for detecting distributed global-scale network attack symptoms in high-speed backbone networks. The proposed method is implemented at the aggregate traffic level. So, our proposed scheme has much lower computational complexity, and is implemented in very high-speed backbone networks. In addition, the proposed method can detect attack patterns, such as attacks in which the target is a certain host or the backbone infrastructure itself, via collaboration of edge routers on the backbone network. The effectiveness of the proposed method are demonstrated via simulation.

• Journal of Power Electronics
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• v.11 no.4
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• pp.520-526
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• 2011

This paper presents a balanced soft-chopping circuit and a modified PI controller for a high speed 4/2 Switched Reluctance Motor (SRM) with a 16 pulse per revolution encoder. The proposed balanced soft-chopping circuit can supply double the switching frequency in the fixed switching frequency of power devices to reduce current ripple. The modified PI controller uses maximum voltage, back-emf voltage and PI control modes to overcome the over-shoot current due to the time delay effect of current sensing. The maximum voltage mode can supply a fast excitation current with consideration of the hardware time delay. Then the back-emf voltage mode can suppress the current over-shoot with consideration of the feedback signal delay. Finally, the PI control mode can adjust the phase current to a desired value with a fast switching frequency due to the proposed balanced soft-chopping technology.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.34S no.8
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• pp.74-83
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• 1997

In this paper, we propose a new fractal image decoding algorithm with fast convergence speed by using the data dependence and the improved initial image estimation. Conventional method for fractal image decoding requires high-degrdd computational complexity in decoding process, because of iterated contractive transformations applied to whole range blocks. On proposed method, Range of reconstruction imagte is divided into referenced range and data dependence region. And computational complexity is reduced by application of iterated contractive transformations for the referenced range only. Data dependence region can be decoded by one transformations when the referenced range is converged. In addition, more exact initial image is estimated by using bound () function in case of all, and an initial image more nearer to a fixed point is estimated by using range block division estimation. Consequently, the convergence speed of reconstruction iamge is improved with 40% reduction of computational complexity.

• Journal of Ubiquitous Convergence Technology
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• v.2 no.1
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• pp.12-17
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• 2008

In this paper, the 128bit AES block cipher algorithm OCB (Offset Code Book) mode for privacy and authenticity of high speed packet data was efficiently designed in C language level and was optimized to support the required capacity of contents server using high performance DSP. It is known that OCB mode is about two times faster than CBC-MAC mode. As an experimental result, the encryption / decryption speed of the implemented block cipher was 308Mbps, 311 Mbps respectively at 1GHz clock speed, which is 50% faster than a general design with 3.5% more memory usage.

• Journal of the Semiconductor & Display Technology
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• v.18 no.3
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• pp.140-143
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• 2019

The Internet has been expanded constantly and greatly such that we are having vast number of web pages with dynamic changes. Especially, the fast development of wireless communication technology and the wide spread of various smart devices enable information being created at speed and changed anywhere, anytime. In this situation, web crawling, also known as web scraping, which is an organized, automated computer system for systematically navigating web pages residing on the web and for automatically searching and indexing information, has been inevitably used broadly in many fields today. This paper aims to implement a prototype web crawler with Python and to improve the execution speed using threads on multicore CPU. The results of the implementation confirmed the operation with crawling reference web sites and the performance improvement by evaluating the execution speed on the different thread configurations on multicore CPU.

• Journal of Multimedia Information System
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• v.6 no.1
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• pp.1-6
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• 2019

In the field of industrial applications, the real-time performance of the target detection problem is very important. The most serious time consumption in the pedestrian detection process is the extraction phase of the candidate window. To accelerate the speed, in this paper, a fast extraction of pedestrian candidate window based on the BING (Binarized Normed Gradients) algorithm replaces the traditional sliding window scanning. The BING features are extracted with the positive and negative samples and input into the two-stage SVM (Support Vector Machine) classifier for training. The obtained BING template may include a pedestrian candidate window. The trained template is loaded during detection, and the extracted candidate windows are input into the classifier. The experimental results show that the proposed method can extract fewer candidate window and has a higher recall rate with more rapid speed than the traditional sliding window detection method, so the method improves the detection speed while maintaining the detection accuracy. In addition, the real-time requirement is satisfied.