• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.15 no.10 s.89
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• pp.1005-1010
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• 2004

An analysis method of slot-coupled microstripline to waveguide transition is presented to developed a simple but accurate equivalent circuit model. The equivalent circuit consists of an ideal transformer, microstrip open stub, and admittance elements looking into a waveguide and a half space of feed side from a slot center. The related circuit element values are calculated by applying the reciprocity theorem, the Fourier transform and series representation, the complex power concept, and the spectral-domain immittance approach. The computed scattering parameters are compared with the measured, and good agreement validates the simplicity and accuracy of the proposed equivalent circuit model.

• Journal of the Institute of Convergence Signal Processing
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• v.8 no.3
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• pp.178-184
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• 2007

The EEG signal in general can be categorized as the Alpha wave, the Beta wave, the Theta wave, and the Delta wave. The alpha wave, showed in stable state, is the dominant wave for a human EEG and the beta wave displays the excited state. The subject of this paper was to recognize the stable state of EEG quantitatively using wavelet transform and power spectrum analysis. We decomposed EEG signal into the alpha wave and the beta wave in the process of wavelet transform, and calculated each power spectrum of EEG signal, using Fast Fourier Transform. And then we calculated the stable state quantitatively by stable state ratio, defined as the power spectrum of the alpha wave over that of the beta wave. The study showed that it took more than 10 minutes to reach the stable state from the normal activity in 69 % of the subjects, 5 -10 minutes in 9%, and less than 5 minutes in 16 %.

• Journal of KIISE
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• v.41 no.12
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• pp.1050-1057
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• 2014

Electroencephalogram (EEG)-based brain-computer interfaces (BCI) can be used for a number of purposes in a variety of industries, such as to replace body parts like hands and feet or to improve user convenience. In this paper, we propose a method to decompose and extract motor imagery EEG signal using Empirical Mode Decomposition (EMD) and Fast Fourier Transforms (FFT). The EEG signal classification consists of the following three steps. First, during signal decomposition, the EMD is used to generate Intrinsic Mode Functions (IMFs) from the EEG signal. Then during feature extraction, the power spectral density (PSD) is used to identify the frequency band of the IMFs generated. The FFT is used to extract the features for motor imagery from an IMF that includes mu rhythm. Finally, during classification, the Support Vector Machine (SVM) is used to classify the features of the motor imagery EEG signal. 10-fold cross-validation was then used to estimate the generalization capability of the given classifier., and the results show that the proposed method has an accuracy of 84.50% which is higher than that of other methods.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.20 no.1
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• pp.22-29
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• 2016

Many studies in detection and classification of the targets in the underwater environments have been conducted for military purposes, as well as for non-military purpose. Due to the complicated characteristics of underwater acoustic signal reflecting multipath environments and spatio-temporal varying characteristics, active sonar target detection technique has been considered as a difficult technique. In this paper, we describe the basic concept of Fractional Fourier transform and optimal transform order. Then we analyze the relationship between time-frequency characteristics of an LFM signal and its spectrum using Fractional Fourier transform. Based on the analysis results, we present active sonar target detection method. To verify the performance of proposed methods, we compared the results with conventional FFT-based matched filter. The experimental results demonstrate the superiority of the proposed method compared to the conventional method in the aspect of AUC(Area Under the ROC Curve).

• Journal of Advanced Navigation Technology
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• v.7 no.2
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• pp.141-148
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• 2003

This paper presents and compares several techniques that detect the symbol rate of unknown received signal. Symbol rate is detected from the power spectral density of the circuits such as the delay and multiplier circuit, the square law circuit, and analytic signal, etc. As a result of discrete Fourier transform of the output signals of these circuits, a lot of spectral lines and some peaks appear in frequency domain and the position of first peak is corresponding to the symbol rate. If a spectral line on the frequency that is not located in symbol rate is larger than the first peak, the symbol rate is erroneously detected. Thus, the ratio between the value of first peak and the highest side spectral line is used for the measure of the performance of symbol rate detector. For the MPSK modulation, the analytic signal method shows better performance than the delay and multiplier and square law circuits when the received signal power is lager than -20dB. It is also noted that the delay and multiplier circuit is not able to detect the symbol rate for the QAM modulation.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.48 no.4
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• pp.160-168
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• 2011

A Frequency domain beamforming technique is widely used in sonar systems with a large number of beams and sensors. In the battlefield environment requiring real-time signal processing, it is needed to optimize the computational complexity of the spectrum computation to implement an efficient and fast frequency domain beamformer. So, in this paper, we proposed the pruned-GSFFT (pruned generalized sliding fast Fourier transform) as a new spectrum computation method. The proposed method help to reduce the computational complexity of the real-time partial spectrum computation by eliminating the redundancy between consecutive input samples and skipping the regardless frequency bands. Also the characteristics of the proposed pruned-GSFFT method and its computational complexity are compared to those of previous FFT algorithms.

• The Journal of the Korea institute of electronic communication sciences
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• v.15 no.6
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• pp.1037-1044
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• 2020

Since radar wind profiler (RWP) provides wind field data with high time and space resolution in all weather conditions, their verification of the accuracy and quality is essential. The simultaneous wind measurement from rawinsonde is commonly used to evaluate wind vectors from RWP. In this study, the simulation algorithm which produces the spectrum and raw time series (I/Q) data from the average values of moments is presented as a step-by-step verification method for the signal processing algorithm. The possibility of the simulation algorithm was also confirmed through comparison with the raw data of LAP-3000. The Doppler power spectrum was generated by assuming the density function of the skew-normal distribution and by using the moment values as the parameter. The simulated spectrum was generated through random numbers. In addition, the coherent averaged I/Q data was generated by random phase and inverse discrete Fourier transform, and raw I/Q data was generated through the Dirichlet distribution.

• Journal of the Korean Society of Radiology
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• v.16 no.4
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• pp.395-403
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• 2022

Flat-panel detector (FPD) used in digital radiographic imaging systems was used to perform a quantitative power spectrum evaluation as a result of the thickness change of polymethyl methacrylate (PMMA), a tissue equivalent. As the PMMA thickness increases with the resolution-chart phantom image, the effect of the scattering line increases, indicating that the modulation characteristics decrease, and the image is bright. The results show that the noise of the image increases, and noise-power spectral images are obtained by Fourier transform to confirm by spatial frequency. Thus, it can be verified that the PMMA thickness and noise are proportional through the result of evaluating the change of resolution characteristics and representing the 2D noise-power spectrum as one-dimensional values by evaluating the change of scattering line with MTF as the PMMA thickness increases in the image.

• The Journal of the Korea institute of electronic communication sciences
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• v.5 no.4
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• pp.363-371
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• 2010

In an effort to enhance the quality of feature vector classification and thereby reduce the recognition error rate for the speaker-independent speech recognition, we study the effect of spectral tilt on the Fourier magnitude spectrum en route to the extraction of MFCC. The effect of FIR filtering on the speech signal on the speech recognition is also investigated in parallel. Evaluation of the proposed methods are performed by two independent ways of the Fisher discriminant objective function and speech recognition test by hidden Markov model with fuzzy vector quantization. From the experiments, the recognition error rate is found to show about 10% relative improvements over the conventional method by an appropriate choice of the tilt factor.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.14 no.6
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• pp.503-511
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• 2004

In this study, for estimating responses of a controlled structure and determining the maximum control force of velocity-dependent damping devices, three estimation models such as Fourier envelope convex model, probability model, and Newmark design spectrum are used. For this purpose, a procedure is proposed for estimating actual velocity using pseudo-velocity and this procedure considers the effects of damping ratio increased by the damping device. Time history results indicate that actual velocity should be used for estimating accurate maximum control force of damping device and Newmark design spectrum modified by the proposed equation gives the best estimation results for over all period structures.