• Journal of electromagnetic engineering and science
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• v.16 no.1
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• pp.19-23
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• 2016

This paper presents a novel design for dual-band bandpass filters. The proposed filters are applicable to the carrier aggregation of the TV white space (TVWS) band and long-term evolution (LTE) band for cognitive radio applications. The lower passband is the TVWS band (470-698 MHz) whose fractional bandwidth is 40 %, while the higher passband is the LTE band (824-894 MHz) with 8 % fractional bandwidth. Since the two passbands are located very close to each other, a transmission zero is inserted to enhance the rejection level between the two passbands. The TVWS band filter is designed using magnetic coupling to obtain a wide bandwidth, and the LTE band filter is designed using dielectric resonators to achieve good insertion loss characteristics. In addition, in the proposed design, a transmission zero is placed with cross-coupling. The proposed dual-band bandpass filter is designed as a two-port filter (one input/one output) as well as a three-port filter (one common input/two outputs). The measured performances show good agreement with the simulated performances.

• Journal of electromagnetic engineering and science
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• v.13 no.2
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• pp.93-103
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• 2013

This paper presented a novel approach for the design of a tunable dual-band bandpass filter (BPF) with independently tunable passband center frequencies and bandwidths. The newly proposed dual-band filter principally comprised two dual-mode single band filters using common input/output lines. Each single BPF was realized using a varactor-loaded transmission line resonator. To suppress the harmonics over a broad bandwidth, a defected ground structure was used at the input/output feeding lines. From the experimental results, it was found that the proposed filter exhibited the first passband center frequency tunable range from 1.48 to 1.8 GHz with a 3-dB fractional bandwidth (FBW) variation from 5.76% to 8.55%, while the second passband center's frequency tunable range was 2.40 to 2.88 GHz with a 3-dB FBW variation from 8.28% to 12.42%. The measured results of the proposed filters showed a rejection level of 19 dB up to more than 10 times the highest center frequency of the first passband.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.46 no.3
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• pp.44-51
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• 2009

This paper addresses a face verification method using the nonlinear composite filter. This face verification process can be simple and speedy because it does not require any reprocessing such as face detection, alignment or cropping. The optimum nonlinear composite filter is derived by minimizing the output energy due to additive noise and an input scene while maintaining the outputs of training images constant. The filter is equipped with the discrimination capability and the robustness to additive noise by minimizing the outputs of the input scene and the noise, respectively. We build the nonlinear composite filter with two training images and compare the filter with the conventional synthetic discriminant function (SDF) filter. The receiver operating characteristics (ROC) curves are presented as a metric for the performance evaluation. According to the experimental results the optimum nonlinear composite filter is shown to be a robust scheme for face verification in low resolution and noise environments.

• International journal of advanced smart convergence
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• v.5 no.4
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• pp.66-70
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• 2016

When tooth grinding occurs, electrical stimulation is given at the same time, and tooth grinding stops on such stimulation. Electromyography signals are used as control signals of electrical stimulation to disturb tooth grinding. However because of the electrical stimulation, the M-waves are generated and mixed with spontaneous electromyogram. In this study, we designed an optimal filter to remove M-wave and conserve spontaneous electromyogram simultaneously. The inverse power method (IPM) showed that the optimal filter coefficient is the eigenvector corresponding to the minimum eigenvalue of the input covariance matrix. In order to evaluate the performance of the optimal filter, we compared using a conventional band pass filter and adaptive filter using least mean square algorithm. The experimental results show that the optimal filter can effectively remove the M-wave compared to the previously studied prediction error filter.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.10 no.5
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• pp.435-441
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• 2017

Detecting an inter-harmonic accurately is not easy work, because it has small magnitude, and its frequency which can be observed is not an integer multiple of fundamental frequency. In this paper, a new method using filter bank system and adaptive predictor is proposed. Filter bank system decomposes input signal to sub bands. In adaptive predictor, inter-harmonic is detected with decomposed sub band signal as input, and error signal as output. In this scheme, input-output characteristic of adaptive predictor is notch filter, as predicted harmonic is canceled in error signal, so detecting an inter-harmonic can be possible. Magnitude and frequency of detected inter-harmonic is estimated by recursive algorithm. The performances of proposed method are evaluated to sinusoidal signal model synthesized with harmonics and inter-harmonics. And validity of the method is proved as comparing the inter-harmonic detection results to MUSIC and ESPRIT.

• The Journal of the Acoustical Society of Korea
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• v.20 no.8
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• pp.3-11
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• 2001

This paper describes an implementation of inverse filter using SVD in order to recover the input in multi-channel system. The matrix formulation in SISO system is extended to MIMO system. In time and frequency domain we investigates the inversion of minimum phase system and non-minimum phase system. To execute an effective inversion of non-minimum phase system, SVD is introduced. First of all we computes singular values of system matrix and then investigates the phase property of system. In case of overall system is non-minimum phase, system matrix has one (or more) very small singular value (s). The very small singular value (s) carries information about phase properties of system. Using this property, approximate inverse filter of overall system is founded. The numerical simulation shows potentials in use of the inverse filter.

• The Journal of the Korea Contents Association
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• v.6 no.12
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• pp.89-95
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• 2006

The performance of blind source separation(BSS) using independent component analysis (ICA) declines significantly in a reverberant environment. A post-processing method proposed in this paper was designed to remove the residual component precisely. The proposed method used modified NLMS(normalized least mean square) filter in frequency domain, to estimate cross-talk path that causes residual cross-talk components. Residual cross-talk components in one channel is correspond to direct components in another channel. Therefore, we can estimate cross-talk path using another channel input signals from adaptive filter. Step size is normalized by input signal power in conventional NLMS filter, but it is normalized by sum of input signal power and error signal power in modified NLMS filter. By using this method, we can prevent misadjustment of filter weights. The estimated residual cross-talk components are subtracted by non-stationary spectral subtraction. The computer simulation results using speech signals show that the proposed method improves the noise reduction ratio(NRR) by approximately 3dB on conventional FDICA.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.2033-2036
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• 2004

A novel approach to estimate the real time moving trajectory of an object is proposed in this paper. The object position is obtained from the image data of a CCD camera, while a state estimator predicts the linear and angular velocities of the moving object. To overcome the uncertainties and noises residing in the input data, a Kalman filter and neural networks are utilized. Since the Kalman filter needs to approximate a non-linear system into a linear model to estimate the states, there always exist errors as well as uncertainties again. To resolve this problem, the neural networks are adopted in this approach, which have high adaptability with the memory of the input-output relationship. Kohonen Network(Self-Organized Map) is selected to learn the motion trajectory since it is spatially oriented. The superiority of the proposed algorithm is demonstrated through the real experiments.

• Proceedings of the IEEK Conference
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• 2002.07a
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• pp.353-356
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• 2002

In this paper, we design an efficient, scalable one-dimensional discrete wavelet transform (1DDWT) filter using data reorder unit (DRU). At each level, the required hardware is optimized by sharing multipliers and adders because the input rate is reduced by a factor of two at each level due to decimation. The proposed architecture shows 100% hardware utilization by balancing hardware with input rate. Furthermore, sharing the coefficients of the highpass and the lowpass filters using the mirror filter property reduces the number of multipliers and adders by half. We designed a scalable DRU that efficiently reorders and feeds inputs to highpass and lowpass filters. The proposed DRU-based architecture is so regular and scalable that it can be easily extended to an arbitrary 1D DWT structure with M taps and J levels. Compared to other architectures, the proposed DWT filter shows efficiency in performance with relatively less hardware.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.10 no.12
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• pp.2303-2307
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• 2006

The round off noise properties of wave digital filters have known and desirable properties in respect to their realization with short coefficient wordlengths. This paper presents the optimal implementation of wave digital filters by employing multiprocessor archtectures in the sense of input sampling rate, the number of processors, and input-output delay. The implementation will be specified by complete circuit diagrams including control signals, and can be applied to an existing silicon complier for VLSI layout generation.