• Proceedings of the Korean Magnestics Society Conference
• /
• 2011.12a
• /
• pp.7-8
• /
• 2011

Although yttrium iron garnet (YIG) has provided a great vehicle for the study of spin waves in the past, associated difficulties in film deposition and device fabrication using YIG had limited the applicability of spin waves to practical devices. However, microfabrication techniques have made it possible to characterize both the resonant as well as the travelling characteristics of spin waves in permalloy (Py). A variety of methods have been used for measuring spin waves, including Brillouin light scattering (BLS), magneto-optic Kerr effect (MOKE), vector network analyzer ferromagnetic resonance (VNA-FMR), and pulse inductive microwave magnetometry (PIMM). PIMM is one of the most preferred methodologies of measuring travelling spin waves. In this method, an electrical impulse is applied at one of two coplanar waveguides patterned on top of oxide-insulated Py, producing a local disturbance in the magnetization of the Py. The resulting disturbance travels down the Py in the form of waves, and is inductively picked up by the other coplanar waveguide. We investigate the effect of the pulse width of excitation pulses on the generated spin wave packets using both experimental results and micromagnetic simulations. We show that spin wave packets generated from electrical pulses are a superposition of two separate spin wave packets, one generated from the rising edge and the other from the falling edge, which interfere either constructively or destructively with one another, depending upon the magnitude and direction of the field bias conditions. A method of spin wave amplitude modulation is also presented by the linear superposition of spin waves. We use interfering spin waves resulting from two closely spaced voltage impulses for the modulation of the magnitude of the resultant spin wave packets.

• The Proceedings of the Korean Institute of Illuminating and Electrical Installation Engineers
• /
• v.11 no.6
• /
• pp.64-73
• /
• 1997

RPWM(Random Pulse Width Modulation) techniques have been attracting an interest as an excellent reduction method of acoustic noise on the inverter drive system. Using randomly changed switching fre-quency of the inverter, the power spectrum of the electromagnetic acoustic noise can be spread out into the wide-band area. The wide band noise is much more comfortable and less annoying than the narrow-band one. This paper describes an implementationof the triangular carrier frequency modultde RPWM inverter drive system The poweer soedtrum of the noise emittde from the induction motro was measured in the anechoic chamber. The analysis of the sources for the acoustic noise and the effects of the noise reduction are confirmed by the ceasured dpectra of the noise. Real-time RPWM along with the speed control was achieved by high speed DSP(Digital Signal Processor ) TmS320C31, By changing the center frequency and the bandwidth of the carrier, theis real-time RPWM scheme can be used as an efficient switching frequency band acoustic noise reduction method for the inverter system with variant load conditions.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.6 no.1
• /
• pp.14-24
• /
• 2002

In this paper, a design of the pulsewidth-modulation(PWM) neural network with both retrieving and learning function is proposed. In the designed PWM neural system, the input and output signals of the neural network are represented by PWM signals. In neural network, the multiplication is one of the most commonly used operations. The multiplication and summation functions are realized by using the PWM technique and simple mixed-mode circuits. Thus, the designed neural network only occupies the small chip area. By applying some circuit design techniques to reduce the nonideal effects, the designed circuits have good linearity and large dynamic range. Moreover, the delta learning rule can easily be realized. To demonstrate the learning capability of the realized PWM neural network, the delta learning nile is realized. The circuit with one neuron, three synapses, and the associated learning circuits has been designed. The HSPICE simulation results on the two learning examples on AND function and OR function have successfully verified the function correctness and performance of the designed neural network.

• The Transactions of the Korean Institute of Power Electronics
• /
• v.11 no.4
• /
• pp.293-301
• /
• 2006

This paper proposes a control algorithm for STATic synchronous COMpensator(STATCOM), based on Space Vector Modulation(SVM) and Hysteresis Current Controller(HCC) techniques. STATCOM is used to reactive power compensation on a distribution network. The proposed algorithm utilizes the advantages of the fast dynamic response of the hysteresis current control and the reduced switching number of the SVM scheme. The controller determines a set of space vectors from a region detector and applies a space vector. A set of space vectors including the zero vector, to reduce the number of switching, is determined from output signals of two hysteresis comparators. The presented control system was tested with digital simulation in the Borland C++ program and demonstrate the advantage of the proposed hysteresis current controller.

• The Journal of the Acoustical Society of Korea
• /
• v.38 no.4
• /
• pp.371-377
• /
• 2019

In this paper, we present the sea trial results of long distance underwater acoustic communication in the East Sea, October 2018. One transmitter and sixteen vertical array receivers were used to collect underwater acoustic communication signals, and the maximum distance between the transmitter and the receiver was 90 km. Information was transmitted by BFSK (Binary Frequency Shift Keying) and BCSK (Binary Chirp Shift Keying) method, which are typical digital frequency modulation techniques. Experimental results show that there is no error in all cases at the transmission distance of 60 km, and BFSK and BCSK have average uncoded bit error rate of 0.0197 and 0.0007 respectively without channel coding at 90 km transmission distance.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.26 no.8
• /
• pp.1222-1230
• /
• 2022

As the number of signal sources with low detectability by using various modulation techniques increases, research to classify signal modulation methods is steadily progressing. Recently, a Convolutional Neural Network (CNN) deep learning technique using FFT as a preprocessing process has been proposed to improve the performance of received signal classification in signal interference or noise environments. However, due to the characteristics of the FFT in which the window is fixed, it is not possible to accurately classify the change over time of the detection signal. Therefore, in this paper, we propose a CNN model that has high resolution in the time domain and frequency domain and uses wavelet transform as a preprocessing process that can express various types of signals simultaneously in time and frequency domains. It has been demonstrated that the proposed wavelet transform method through simulation shows superior performance regardless of the SNR change in terms of accuracy and learning speed compared to the FFT transform method, and shows a greater difference, especially when the SNR is low.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.17 no.1
• /
• pp.239-260
• /
• 2023

The underwater acoustic wireless communication networks are generally formed by the different autonomous underwater acoustic vehicles, and transceivers interconnected to the bottom of the ocean with battery deployed modems. Orthogonal frequency division multiplexing (OFDM) has become the most popular modulation technique in underwater acoustic communication due to its high data transmission and robustness over other symmetrical modulation techniques. To maintain the operability of underwater acoustic communication networks, the power consumption of battery-operated transceivers becomes a vital necessity to be minimized. The OFDM technology has a major lack of peak to average power ratio (PAPR) which results in the consumption of more power, creating non-linear distortion and increasing the bit error rate (BER). To overcome this situation, we have contributed our symmetry research into three dimensions. Firstly, we propose a machine learning-based underwater acoustic communication system through long short-term memory neural network (LSTM-NN). Secondly, the proposed LSTM-NN reduces the PAPR and makes the system reliable and efficient, which turns into a better performance of BER. Finally, the simulation and water tank experimental data results are executed which proves that the LSTM-NN is the best solution for mitigating the PAPR with non-linear distortion and complexity in the overall communication system.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.31 no.8A
• /
• pp.745-751
• /
• 2006

The transmitter requires knowledge of the channel status information in order to adopt the adaptive modulation and coding scheme(AMC) for OFDM system. But in the outdoor environment which the users have high mobility, the channel status information from the users is outdated, so that it induces the degradation of system throughput and packet error rate(PER) performance. To solve this problem, researches about applying channel prediction technique to the AMC scheme have been proceeded. Most channel prediction techniques assume that there is no channel variation in the predefined time duration, e.g., a slot. As a result, those techniques cannot compensate the degradation of PER performance resulting from the rapid variation of channel during the slot duration. This paper introduces a novel channel prediction technique for OFDM/FDD system to support adaptive modulation and coding scheme over rapidly time-varying multipath fading channel. The proposed channel prediction technique considers the time-varying nature of channel during the slot duration. Simulation results show that the AMC scheme of OFDM/FDD system utilizing the proposed channel prediction technique can guarantee the target PER of 1% without any loss of system throughput compared with the case supported by the conventional channel prediction under ITU-R Veh A 30km/h.

• Investigative Magnetic Resonance Imaging
• /
• v.7 no.1
• /
• pp.12-21
• /
• 2003

Purpose : In order to overcome limitations in the existing conventional spectrometer, a new spectrometer with advanced functionalities is designed and implemented. Materials and Methods : We designed a spectrometer using the TMS320C6701 DSP capable of 1 giga floating point operations per second (GFLOPS). The spectrometer can generate continuously varying complicate gradient waveforms by real-time calculation, and select image plane interactively. The designed spectrometer is composed of two parts: one is DSP-based digital control part, and the other is analog part generating gradient and RF waveforms, and performing demodulation of the received RF signal. Each recover board can measure 4 channel FID signals simultaneously for parallel imaging, and provides fast reconstruction using the high speed DSP. Results : The developed spectrometer was installed on a 1.5 Tesla whole body MRI system, and performance was tested by various methods. The accurate phase control required in digital modulation and demodulation was tested, and multi-channel acquisition was examined with phase-array coil imaging. Superior image quality is obtained by the developed spectrometer compared to existing commercial spectrometer especially in the fast spin echo images. Conclusion : Interactive control of the selection planes and real-time generation of gradient waveforms are important functions required for advanced imaging such as spiral scan cardiac imaging. Multi-channel acquisition is also highly demanding for parallel imaging. In this paper a spectrometer having such functionalities is designed and developed using the TMS320C6701 DSP having 1 GFLOPS computational power. Accurate phase control was achieved by the digital modulation and demodulation techniques. Superior image qualities are obtained by the developed spectrometer for various imaging techniques including FSE, GE, and angiography compared to those obtained by the existing commercial spectrometer.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
• /
• v.18 no.6 s.121
• /
• pp.602-611
• /
• 2007

In this paper, the forward link of UHF RFID system is modeled in accordance with the EPCglobal class 1 generation 2(EPCglobal C1G2) UHF Radio-Frequency Identity protocol specification at $860{\sim}960MHz$. Based on the constructed model, characteristics on the forward link signal for the EPCglobal C1G2 RFID reader are simulated with the help of a MATLAB softwarein order to extract the design parameters of a transmit digital filter which meets the Korean RFID regulations. Herein, the forward link model is consisted of PIE source coding, transmit digital filter, modulation, local oscillator, and antenna. From the simulation results, the ranges of three design parameters(roll-off factor, cutoff frequency, the number of tabs) for transmit digital filter are obtained with different modulation techniques and the Tari(type a reference interval) values. Finally, DSB/SSB-ASK modulation technique can not satisfy the EPCglobal C1G2 specification when Tari equals to $6.25{\mu}sec$ in a multiple-reader environment. Consequently this paper can provide a guideline for design parameters of a RFID reader as well as the basic scheme of analyzing frequency interference problems in RFID environments, including multiple-reader and dense-reader environments.