• 제어로봇시스템학회:학술대회논문집
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• 1989.10a
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• pp.962-966
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• 1989

A Digital Signal Processor (abbreviated to DSP) is used not only for digital signal processing but also for kinematic controls[l]. Then applications to these fields are expected to be developed. We propose a function calculation method on DSP which occupies no table memory. By using these functions, more fast or more accurate control will be achieved without using function table.

• Proceedings of the Acoustical Society of Korea Conference
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• 1984.12a
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• pp.91-95
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• 1984

Because of layer and scattering in the ocean, there are some problem in algorithm currently used for the recognition of targets. Those are time delay of processing and circuit design. The simple method of detecting direct sound wave in noise caused by time delay is proposed-recognized, estimated, and then direcxt sound wave is reconstructed by the AMDF and $\mu$-processor. 2KHz, 4KHz, 8KHz, 12KHz, 16KHz sound waves are used in experiment. To obtain a reference signal, anechoic water tank is used is processing and aluminium water tank used instead of real ocean. As a result, there are a few errors which caused by anechoic water tank error, decreasing of frequency make errors. Possibility of application to Sonar Signal Processing is proved.

• The Journal of Korea Robotics Society
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• v.2 no.3
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• pp.205-211
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• 2007

In this paper, the prototype of surface EMG (ElectroMyoGram) sensor is developed for the robotic rehabilitation applications, and the developed sensor is composed of the electrodes, analog signal amplifiers, analog filters, ADC (analog to digital converter), and DSP (digital signal processor) for coding the application example. Since the raw EMG signal is very low voltage, it is amplified by about one thousand times. The artifacts of amplified EMG signal are removed by using the band-pass filter. Also, the processed analog EMG signal is converted into the digital form by using ADC embedded in DSP. The developed sensor shows approximately the linear characteristics between the amplitude values of the sensor signals measured from the biceps brachii of human upper arm and the joint angles of human elbow. Finally, to show the performance of the developed EMG sensor, we suggest the application example about the real-time human elbow motion acquisition by using the developed sensor.

• Publications of The Korean Astronomical Society
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• v.22 no.3
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• pp.63-73
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• 2007

In this paper, we introduce the performance test results of digital data processing system for KVN (Korean VLBI Network). The digital data processing system for KVN consists of DAS (Data Acquisition System) and high-speed recorder which called Mark5B system. DAS system performs the digitalization of analog radio signal through ADS-1000 gigabit sampler with 1 Gsps/2-bit and process the digital filtering of digital signal. Mark5B system records the output data of DFB (Digital Filter Bank) with about 1 Gbps. In this paper, we carried out the preliminary evaluation experiments of the KVN digital data processing system connected between DAS system and Mark5B with VSI (VLBI Standard Interface) interface which is designed for compatible in each VLBI system. We first performed all of the KVN digital data processing system connected by VSI interface in the world. In factory inspection phase, we found that the DAS system has a memory read/write error in DSM (Digital Spectrometer) by analyzing the recorded data in Mark5B system. We confirmed that the DSM memory error has been correctly solved by comparing DSM results with Mark5B results. The effectiveness of KVN digital data processing system has been verified through the preliminary experiments such as data transmission, recording with VSI interface connection and data analysis between DSM and Mark5B system. In future work, we will perform the real astronomical observation by using the KVN 21m radio telescopes so as to verify its stability and performance.

• Journal of the Korea Convergence Society
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• v.7 no.3
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• pp.77-85
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• 2016

We propose a digital signal processing technic that can compensate the non-linearity inherent in audio amplifiers, and present the result of the simulation. The inherent non-linearity of the audio power amplifier arising from analog devices is compensated via a digital signal processing technic consisting of indirect learning architecture and an adaptive filter. The simulation results show that the compensator can be realized using a third-order polynomial and compensates odd-order non-linearity efficiently. The even-oder non-linearity is mainly due to the dc offset at the output, which is difficult to eliminate with the proposed method. Care must be taken in designing the bias circuit to avoid the DC offset at the output. The proposed technic has significance in that digital signal processing technic can compensate for the impairment that is an inherent characteristic of an analog system.

• Journal of the Korea Institute of Military Science and Technology
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• v.9 no.3
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• pp.116-122
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• 2006

A fast scan digital-IF FFT receiver at the radio communication band is presented for spectrum monitoring applications. It is composed of three parts: RF front-end, fast LO board, and signal processing board. It has about 19GHz/s scan rate, multi frequency resolution from 10kHz to 2.5kHz, and high sensitivity of below -99dBm. The design and performance analysis of the digital-IF FFT receiver are presented.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2009.10a
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• pp.973-976
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• 2009

Digital signal processing technique use to variety fields including communication. For these signal processing, FIR digital filter is representative. And for FIR digital filter designing, the window function is used to reduce the Gibbs phenomenon which occurs in the coefficient cutting process of the ideal filter. Therefore, in this paper to improve performance of digital filter, a high-order window function was applied. In this simulation, we compared a peak side-lobe and a transient characteristics with the existing window function.

• Proceedings of the Korea Institute of Convergence Signal Processing
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• 2000.08a
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• pp.357-360
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• 2000

In this paper, we want to implement a noise canceller by using FIR filter on DSP(Digital Signal Processor). The FIR filter was designed by Blackman window together with desired band width and center frequency. We adopt Motorola DSP56002 and Crystal CS4215 (A/D and D/A converter) for our purpose. we generate input sinusoidal signals and noises by differential equations and pseudo random sequences on DSP also. The input signal including sinusoidal and noise passes through the FIR filter. The FIR filer output is a sinusoidal signal with noise reduced.

• Proceedings of the Korea Institute of Convergence Signal Processing
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• 2005.11a
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• pp.159-162
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• 2005

Recently, due to rapid developments of wireless communication and digital TV, modern society needs to process of aquisition, storage and transmission of much information. So the importance of signal processing is increasing and various digital filters are used in the two-dimensional signal such as image. And kinds of these digital filters are IIR(infinite impulse response) filter and FIR(finite impulse response) filter. And FIR filter which has the phase linearity, the easiness of creation and stability is applied to many fields. In design of this FIR filter, flatness property is a important factor in pass-band and stop-band. In this paper, we designed a 2-D Circular FIR filter using the Bernstein polynomial, it is presented flatness property in pass-band and stop-band. And we simulated the designed filter with noisy test image and compared the results with existing methods.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1995.10a
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• pp.393-396
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• 1995

In this syudy, the researches classifying the artificial and natural flaws in welding parts are performed using the smart pattern recognition technology. For this purpose the smart signal pattern recognition package including the user defined function was developed and the total procedure including the digital signal processing,feature extraction , feature selection and classifier selection is treated by bulk. Specially it is composed with and discussed using the statistical classifier such as the linear disciminant function classifier, the empirical Bayesian classifier. Also, the smart pattern recognition technology is applied to classification problem of natural flaw(i.e multiple classification problem-crack,lack of penetration,lack of fusion,porosity,and slag inclusion, the planar and volumetric flaw classification problem). According to this results, if appropriately learned the neural network classifier is better than ststistical classifier in the classification problem of natural flaw. And it is possible to acquire the recognition rate of 80% above through it is different a little according to domain extracting the feature and the classifier.