• Journal of information and communication convergence engineering
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• v.21 no.1
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• pp.1-8
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• 2023

This paper presents a design method for a wideband bandpass filter (BPF) which compensates for frequency dependency based on the image admittance and image phase. In the proposed method, new compensation methods for the admittance and phase are integrated with the conventional method. The proposed method improves the frequency shift and reduces the unwanted bandwidth when designing more than 20% of the Fractional Bandwidth (FBW), whereas the conventional method exhibits frequency degradation at only 10% FBW. The proposed design theory was verified by applying it to both lumped elements and distributed lines through circuit simulation and measurements without an optimization process. The measurement results demonstrate improvements in the frequency shift and target bandwidth. In the future, an accurate design method based on frequency dependence can be implemented for the next-generation broadband communication system applications.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.35 no.2
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• pp.143-148
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• 2022

For the purpose of treating health checkups and recovery of patients in a super-aged society, hospitals use devices designed with a reduction circuit of electromagnetic waves associated with the specific absorption rate of electromagnetic waves absorbed by the human body. In this paper, we proposed a filter improvement design method capable of reducing electromagnetic waves. As a result of confirming the validity of the proposed technique through simulation and experimental results, the following result values were obtained. Applying the common-mode (CM) inductor 4 mH to a calibration circuit, noise decreased in a multiband spectrum. Using the differential mode(DM) inductor 40 µH element in the primary calibration circuit, the noise decreased by 15 dB or more in the 3 MHz band spectrum. Also, applying the Admittance Capacitance (Y-Cap) 10 nF element in the secondary calibration circuit resulted in the decrease by more than 30 dB in the band spectrum before 2 MHz. After using a common-mode inductor 4 mH element in the tertiary calibration circuit, it decreased by more than 15 dB in the band spectrum after 2 MHz.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.14 no.7
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• pp.586-603
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• 2004

One of the subtle problems that make noise control difficult for engineers is “the invisibility of noise or sound.” The visual image of noise often helps to determine an appropriate means for noise control. There have been many attempts to fulfill this rather challenging objective. Theoretical or numerical means to visualize the sound field have been attempted and as a result, a great deal of progress has been accomplished, for example in the field of visualization of turbulent noise. However, most of the numerical methods are not quite ready to be applied practically to noise control issues. In the meantime, fast progress has made it possible instrumentally by using multiple microphones and fast signal processing systems, although these systems are not perfect but are useful. The state of the art system is recently available but still has many problematic issues : for example, how we can implement the visualized noise field. The constructed noise or sound picture always consists of bias and random errors, and consequently it is often difficult to determine the origin of the noise and the spatial shape of noise, as highlighted in the title. The first part of this paper introduces a brief history, which is associated with “sound visualization,” from Leonardo da Vinci's famous drawing on vortex street (Fig. 1) to modern acoustic holography and what has been accomplished by a line or surface array. The second part introduces the difficulties and the recent studies. These include de-Dopplerization and do-reverberation methods. The former is essential for visualizing a moving noise source, such as cars or trains. The latter relates to what produces noise in a room or closed space. Another mar issue associated this sound/noise visualization is whether or not Ivecan distinguish mutual dependence of noise in space : for example, we are asked to answer the question, “Can we see two birds singing or one bird with two beaks?"