• Journal of Advanced Navigation Technology
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• v.25 no.4
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• pp.293-298
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• 2021

In general, the guided weapon seeker and the guided control device process the target, search, recognition, and capture information to indicate the state of the guided missile, and play a role in controlling the operation and control of the guided weapon. The signals required for guided weapons are gaze change rate, visual signal, and end-stage fuselage orientation signal. In order to process the complex and difficult-to-process missile signals of recent missiles in real time, it is necessary to increase the data processing speed of the missiles. This study showed the processing speed after applying the stop and go and inverse enumeration algorithm among the parallel algorithm methods of PINQ and comparing the processing speed of the signal data required for the guided missile in real time using the guided missile inspection program. Based on the derived data processing results, we propose an effective method for processing missile data when applying a parallel processing algorithm by comparing the processing speed of the multi-core processing method and the single-core processing method, and the CPU core utilization rate.

• Proceedings of the KIEE Conference
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• 2005.10b
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• pp.306-308
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• 2005

The vehicle detection method using pulse radar has the advantage of maintenance in comparison with loop detection method. We have the information about the vehicle being and position by dividing the signals into sectors in accordance with SSC method, and by applying the discriminant function based on stochastical data. We also reduce the signal processing time.

• Proceedings of the KOSOMBE Conference
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• v.1994 no.05
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• pp.49-52
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• 1994

We have developed a biological signal measurement, archiving, and communication system (SiMACS). The front end of the system is the intelligent data processing unit (IDPU) which includes ECG, EEG, EMG, blood pressure, respiration, temperature measurement modules, module control and data acquisition unit, real-time display and signal processing unit. IDPUS are connected to central data base unit through LAN(Ethernet). Workstations which receive signals from central DB and provide various signal analysis tools are also connected to the network. The developed PC-based SiMACS is described.

• Journal of the Institute of Convergence Signal Processing
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• v.24 no.2
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• pp.90-96
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• 2023

Securing large amounts of training data in deep learning neural networks, including convolutional neural networks, is of importance for avoiding overfitting phenomenon or for the excellent performance. However, securing labeled training data in deep learning neural networks is very limited in reality. To overcome this, several augmentation methods have been proposed in the literature to generate an additional large amount of training data through transformation or manipulation of the already acquired traing data. However, unlike training data such as images and texts, it is barely to find an augmentation method in the literature that additionally generates bio-signal training data for convolutional neural network based human activity recognition. Thus, this study proposes a simple but effective augmentation method of bio-signal training data for convolutional neural network based human activity recognition. The usefulness of the proposed augmentation method is validated by showing that human activity is recognized with high accuracy by convolutional neural network trained with its augmented bio-signal training data.

• The Journal of the Korea institute of electronic communication sciences
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• v.19 no.2
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• pp.335-343
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• 2024

Real-time target signal processing techniques for FMCW LiDAR are described in this paper. FMCW LiDAR is gaining attention as the next-generation LiDAR for self-driving cars because of its detection robustness even in adverse environmental conditions such as rain, snow and fog etc. in addition to its long range measurement capability. The hardware architecture which is required for high-speed data acquisition, data transfer, and parallel signal processing for frequency-domain signal processing is described in this article. Fourier transformation of the acquired time-domain signal is implemented on FPGA in real time. The paper also details the C-FAR algorithm for ensuring robust target detection from the transformed target spectrum. This paper elaborates on enhancing frequency measurement resolution from the target spectrum and converting them into range and velocity data. The 3D image was generated and displayed using the 2D scanner position and target distance data. Real-time target signal processing and high-resolution image acquisition capability of FMCW LiDAR by using the proposed parallel signal processing algorithms based on FPGA architecture are verified in this paper.

• Journal of Institute of Control, Robotics and Systems
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• v.6 no.5
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• pp.396-403
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• 2000

A thermal imaging system is implemented for the measurement and the analysis of the thermal distribution of the target objects. The main part of the system is a thermal camera in which a focal plane array typed sensor is introduced. The sensor detects the mid-range infrared spectrum of target objects and then it outputs a generic video signal which should be processed to form a frame thermal image. Here, a digital signal processor(DSP) is applied for the high speed processing of the sensor signals. The DSP controls analog-to-digital converter, performs correction algorithms and outputs the frame thermal data to frame buffers. With the frame buffers can be generated a NTSC signal and transferred the frame data to personal computer(PC) for the analysis and a monitoring of the thermal scenes. By performing the signal processing functions in the DSP the overall system achieves a simple configuration. Several experimental results indicate the performance of the overall system.

• Journal of Positioning, Navigation, and Timing
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• v.6 no.3
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• pp.87-94
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• 2017

GNSS modernization and development is in progress throughout the globe, and it is focused on the addition of a new navigation signal. Accordingly, for the next-generation GNSS signals that have been developed or are under development, various combinations that are different from the existing GNSS signal structures can be introduced. In this regard, to design an advanced signal, it is essential to clearly understand the effects of the signal structure and design variables. In the present study, the effects of the GNSS spreading code period and GNSS data bit duration (i.e., signal design variables) on the signal processing performance were analyzed when the data bit transition was considered, based on selected GNSS signal design scenarios. In addition, a method of utilizing the obtained result for the design of a new GNSS signal was investigated.

• Proceedings of the KSME Conference
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• 2001.06b
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• pp.42-47
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• 2001

Analyzing the ECG signal, we can find heart disease, for example, arrhythmia and myocardial infarction, etc. Particularly, detecting arrhythmia is more important, because serious arrhythmia can take away the life from patients within ten minutes. In this paper, we would like to introduce the signal processing for ECG analysis and the device made for wireless communication of ECG data. In the signal processing, the wavelet transform decomposes the ECG signal into high and low frequency components using wavelet function. Recomposing the high frequency bands including QRS complex, we can detect QRS complex and eliminate the noise from the original ECG signal. To recognize the ECG signal pattern, we adopted the polynomial approximation partially and statistical method. The ECG signal is divided into small parts based on QRS complex, and then, each part is approximated to the polynomials. Comparing the approximated ECG pattern with the database, we can detect and classify the heart disease. The ECG detection device consists of amplifier, filters, A/D converter and RF module. After amplification and filtering, the ECG signal is fed through the A/D converter to be digitalized. The digital ECG data is transmitted to the personal computer through the RF transceiver module and serial port.

• Journal of Biomedical Engineering Research
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• v.22 no.3
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• pp.285-291
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• 2001

In this paper, we designed two preprocessing adaptive filter - high pass filter and notch filter - using FPGA. For minimizing the calculation load of multi-channel and high-resolution ECG system, we utilize FPGA rather than digital signal processing chip. To implement the designed filters in FPGA, we utilize FPGA design tool(Altera corporation, MAX-PLUS II) and CSE database as test data. In order to evaluate the performance in terms of processing time, we compared the designed filters with the digital filters implemented by ADSP21061(Analog Devices). As a result, the filters implemented by FPGA showed better performance than the filters based on ADSP21061. As a consequence of examination, we conclude that FPGA is a useful solution in multi-channel and high-resolution signal processing.

• Proceedings of the IEEK Conference
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• 1998.06a
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• pp.627-630
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• 1998

In this study, we derived stop-and-go normalized DD, dual-mode normalized sato, dual-mode NCMA blind equalization algorithm for complex data. and then, the convergence characteristics of the proposed SG-NDD, dual-mode NSato blind equalization algorithms are compared with those of SG-DD, dual-mode sato algorithm. In genral, the normalized blind equalization algorithms have better convergence characteristics than the conventional algorithms.