• Journal of Applied Reliability
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• v.8 no.2
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• pp.101-111
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• 2008

Good diagnostics improves both the safety and system unavailability of digital safety systems. The measure of a diagnostic capability is called the Coverage Factor. Because the Failure Modes, Effects and Diagnostic Analysis (FMEDA) provides information on the failure rates and failure mode distributions necessary to calculate a diagnostic coverage factor for a component, the FMEDA can be used as a useful tool to calculate it. Through performing FMEDA on a digital signal processor (DSP) board used in a digital safety system, it is shown that some components of the DSP board can be replaced or improved to satisfy the required diagnostic coverage. That is, the FMEDA can serve as a useful verification tool to design a diagnostic capability for the DSP board.

• International Journal of Ocean System Engineering
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• v.1 no.1
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• pp.52-59
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• 2011

A prototype radar display unit was implemented using inexpensive off-the-shelf components, including a nonlinear estimation algorithm for the target tracking in a clutter environment. Two custom designed boards; an analog signal processing board and a DSP board, can be plugged into an expansion slot of a personal computer (PC) to form a maritime radar display unit. Our system provided all the functionality specified in the International Maritime Organization (IMO) resolution A422(XI). The analog signal processing board was used for A/D conversion as well as rain and sea clutter suppression. The main functions of the DSP board were scan conversion and video overlay operations. A host PC was used to run the tracking algorithm of targets in clutter, using the discrete-time Bayes optimal (nonlinear, and non-Gaussian) estimation method, and the graphic user interface (GUI) software for Automatic Radar Plotting Aid (ARPA). The proposed tracking method recursively found the entire probability density function of the target position and velocity by converting into linear convolution operations.

• Journal of the Korea Institute of Military Science and Technology
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• v.8 no.2 s.21
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• pp.30-37
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• 2005

In this paper, we propose how to design a fire control system main control board for individual combat weapons using a small and low power processor. To design an electric board of small weapon systems, Size and power consumption are very important factors. We solved the problem using selection of an adaptive processor, introduction of MicroChipPackaging method, and separate design of a main board Also we applied these methods to make the fire control system for small arms.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.49 no.1
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• pp.48-53
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• 2000

In this paper, we develop a TMS320C31 (60MHz) digital signal processor (DSP) board to synthesize gradient waveforms for Spiral Scan Imaging (SSI), which is one of the ultra fast magnetic resonance imaging (MRI) methods widely used. In SSI, accurate gradient waveforms are very essential to high quality magnetic resonance images. For this purpose, sampling rate for synthesizing the gradient waveforms is set twice as high as the data sampling rate. With the developed DSP boards accurate gradient waveforms are obtained. Ultra fast spiral scan imaging with the developed with the developed DSP board is currently under development.

• The Journal of the Acoustical Society of Korea
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• v.13 no.2E
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• pp.58-67
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• 1994

Hidden Markov Model (HMM)-based algorithms have been used successfully in many speech recognition systems, especially large vocabulary systems. Although general purpose processors can be employed for the system, they inevitably suffer from the computational complexity and enormous data. Therefore, it is essential for real-time speech recognition to develop specialized hardware to accelerate the recognition steps. This paper concerns with a real-time implementation of an isolated word recognition system based on HMM. The speech recognition system consists of a host computer (PC), a DSP board, and a prototype Viterbi scoring board. The DSP board extracts feature vectors of speech signal. The Viterbi scoring board has been implemented using three field-programmable gate array chips. It employs a hardware-efficient Viterbi scoring architecture and performs the Viterbi algorithm for HMM-based speech recognition. At the clock rate of 10 MHz, the system can update about 100,000 states within a single frame of 10ms.

• Journal of Industrial Technology
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• v.29 no.A
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• pp.95-100
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• 2009

In this paper, we implemented a speaker-independent speech recognizer using the TMS320F28335 DSP which is optimized for control applications. For this implementation, we used a small-sized commercial DSP module and developed a peripheral board including a codec, signal conditioning circuits and I/O interfaces. The speech signal digitized by the TLV320AIC23 codec is analyzed based on MFCC feature extraction methed and recognized using the continuous-density HMM. Thanks to the internal SRAM and flash memory on the TMS320F28335 DSP, we did not need any external memory devices. The internal flash memory contains ADPCM data for voice response as well as HMM data. Since the TMS320F28335 DSP is optimized for control applications, the recognizer may play a good role in the voice-activated control areas in aspect that it can integrate speech recognition capability and inherent control functions into the single DSP.

• Journal of Digital Convergence
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• v.16 no.7
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• pp.223-229
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• 2018

Recently, the necessity of safety diagnosis of electrical devices has been increasing as the fire caused by electric devices has increased rapidly. This study is concerned with the safety diagnosis of electric equipment using intelligent Fuzzy technology. It is used as a diagnostic input for the multiple electrical safety factors such as the use current, cumulative use time, deterioration and arc characteristics inherent to the equipment. In order to extract these information in real time, a device composed of various sensor circuits, DSP signal processing, and communication circuit is implemented. The fuzzy logic algorithm using the Gaussian function for each information is designed and compiled to be implemented on a small DSP board. The fuzzy logic receives the four diagnostic information, deduces it by the fuzzy engine, and outputs the overall safety status of the device as a 100-step analog fuzzy value familiar to human sensibility. By experiments of a device that combines hardware and fuzzy algorithm implemented in this study, it is verified that it can be implemented in a small DSP board with human-friendly fuzzy value, diagnosing real-time safety conditions during operation of electric equipment. In the future, we expect to be able to study more intelligent diagnostic systems based on artificial intelligent with AI dedicated Micom.

• Journal of the Institute of Convergence Signal Processing
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• v.11 no.4
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• pp.263-269
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• 2010

This paper describes real-time detection and tracking of moving objects for unmanned visual surveillance. Using images obtained from the fixed camera it detects moving objects within the image and tracks them with displaying rectangle boxes enclosing the objects. Tracking method is implemented on an embedded system which consists of TI DSK645.5 kit and the FPGA board connected on the DSP kit. The DSP kit processes image processing algorithms for detection and tracking of moving objects. The FPGA board designed for image acquisition and display reads the image line-by-line and sends the image data to DSP processor, and also sends the processed data to VGA monitor by DMA data transfer. Experimental results show that the tracking of moving objects is working satisfactorily. The tracking speed is 30 frames/sec with 320x240 image resolution.

• International Journal of Precision Engineering and Manufacturing
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• v.4 no.1
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• pp.9-14
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• 2003

In this study we suggest real-time simulator that could describe rent system without ordinary DSP card. This simulator is composed of 80196kc-16bit ordinary microprocessor, which is widely used up to now and personal computer. DSP card that has calculated complex numerical equation is replaced by personal computer and 80196kc generates control signals independently out of the personal computer. In all process personal computer is synchronized with one-board microprocessor (80196kc) within sampling time in the closed loop system. This makes it possible to be described in hydraulic servo system in real time.

• Journal of Biomedical Engineering Research
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• v.24 no.1
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• pp.45-53
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• 2003

Based on the 4-compartmental pharmacokinetic model developed in PART1, target-controlled infusion(TCI) pump system was designed and evaluated. The TCI system consists of digital board including microcontroller and digital signal process(DSP), analog board, motor-driven actuator, user friendly interface, power management and controller. It provides two modes according to the drugs: plasma target concentration and effect target concentration. Anaesthetist controls the depth of anaesthesia for patients by adjusting the required concentration to maintain both plasma and effect site in drug concentration. The data estimated in DSP include infusion rate, initial load dose, and rotation number of motor encoder. During TCI operation, plasma concentration. effect site concentration, awaken concentration, context-sensitive decrement time and system error information are displayed in real time. Li-ion battery guarantees above 2 hours without power line failure. For high reliability of the system, two microprocessors were used to perform independent functions for both pharmacokinetic algorithm and motor control strategy.