• Journal of the Semiconductor & Display Technology
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• v.22 no.4
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• pp.53-58
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• 2023

The storage capacity of 3D-NAND flash memory has been enhanced by the multi-layer dielectrics. The deposition process has become more challenging due to the tight process margin and the demand for accurate process control. To reduce product costs and ensure successful processes, process diagnosis techniques incorporating artificial intelligence (AI) have been adopted in semiconductor manufacturing. Recently there is a growing interest in process diagnosis, and numerous studies have been conducted in this field. For higher model accuracy, various process and sensor data are required, such as optical emission spectroscopy (OES), quadrupole mass spectrometer (QMS), and equipment control state. Among them, OES is usually used for plasma diagnostic. However, OES data can be distorted by viewport contamination, leading to misunderstandings in plasma diagnosis. This issue is particularly emphasized in multi-dielectric deposition processes, such as oxide and nitride (ON) stack. Thus, it is crucial to understand the potential misunderstandings related to OES data distortion due to viewport contamination. This paper explores the potential for misunderstanding OES data due to data distortion in the ON stack process. It suggests the possibility of excessively evaluating process drift through comparisons with a QMS. This understanding can be utilized to develop diagnostic models and identify the effects of viewport contamination in ON stack processes.

• Proceedings of the KIEE Conference
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• 2004.11c
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• pp.261-264
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• 2004

In this paper, we identify the memory effect of high power(125W) laterally diffused metal oxide-semiconductor(LDMOS) RF Power Amplifier(PA) by two tone IMD measurement. We measure two tone IMD by changing the tone spacing and the power level. Different asymmetric IMD is founded at different center frequency measurements. We propose the Tapped Delay Line-Neural Network(TDNN) technique as the modeling method of LDMOS PA based on two tone IMD data. TDNN's modeling accuracy is highly reasonable compared to the memoryless adaptive modeling method.

• Journal of the Korean Institute of Telematics and Electronics A
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• v.31A no.6
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• pp.61-69
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• 1994

For distortion-invariant recognition of Korean characters, a holographic implementation of an optical associative memory system is proposed. The structure of the proposed system is a single-layer neural network employing interconneclion matrix, thresholding and feedback. To provide the interconnection matrix, we use two CGII's which are placed on intermcdiate plane of cascaded Vander Lugt corrclators to form an optical memory loop. The holographic correlator stores reference images in a hologram and retrives them in a coherently illuminated feedback loop. An input image which maybe noisy or incomplete, is applicd to the system and simultaneously correlated optically with all of the stord images. These correlations are throsholed and fed back to the input, where the strongest correlation reinforces the input image. The enhanced image passes arround the loop repeatedly, approaching the stored image more closely on each pass until the system stabilizes on the desired image. The computer simulation results show that the proposed Korean Character recognition algorithm has high discrimination capability and noise immunity.

• Asian-Australasian Journal of Animal Sciences
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• v.18 no.6
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• pp.868-872
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• 2005

Individual management of the animal is the first step towards reaching the goal of precision livestock farming that aids animal welfare. Accurate recognition of each individual animal is important for precise management. Electronic identification of cattle, usually referred to as RFID (Radio Frequency Identification), has many advantages for farm management. In practice, however, RFID implementations can cause several problems. Reading speed and distance must be optimized for specific applications. Image processing is more effective than RFID for the development of precision farming system in livestock. Therefore, the aim of this paper is to attempt the identification of cattle by using image processing. The majority of the research on the identification of cattle by using image processing has been for the black-and-white patterns of the Holstein. But, native Japanese and Korean cattle do not have a consistent pattern on the body, so that identification by pattern is impossible. This research aims to identify to Japanese black cattle, which does not have a black-white pattern on the body, by using image processing and a neural network algorithm. 12 Japanese black cattle were tested. Values of input parameter were calculated by using the face image values of 12 cows. The face was identified by the associate neural memory algorithm, and the algorithm was verified by the transformed face image, for example, of brightness, distortion, noise and angle. As a result, there was difference due to a transformation ratio of the brightness, distortion, noise, and angle. The algorithm could identify 100% in the range from -30 to +30 degrees of brightness, -20 to +40 degrees of distortion, 0 to 60% of noise and -20 to +30 degree of angle transformed images.

• Journal of Satellite, Information and Communications
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• v.8 no.2
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• pp.88-93
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• 2013

The wideband chirp signal generator to enhance the resolution of synthetic aperture radar of obtaining the earth observation image is needed. This paper deals with designing, manufacturing and testing the wideband digital chirp signal generator having high resolution for LEO earth observation satellite. The wideband digital chirp signal generator is implemented with the memory-map based structure which is mostly applied in the satellite, and consists of the digital module to generate the digital chirp signal and the RF module to perform the quadrature modulation. The I/Q signals stored in the memory of the digital module are D/A converted and delivered to be quadrature modulated with the reference signal of 1275 MHz in the RF module. Furthermore, the test bench and GUI to validate the signal generator function are also developed. It is found that the requirement of 144 MHz bandwidth for the digital chirp signal generator is well met. Finally it is noteworthy that the distortion occurred in the chirp signal generator was compensated by the pre-distortion compensation.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.1
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• pp.239-260
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• 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
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• v.28 no.3C
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• pp.286-295
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• 2003

In this paper, the wavelet image coder, that can encode the image to various bit rate with minimum memory usage, is proposed. The proposed coder is used the 2D significant coefficient array(SCA) that has bit level informal on of the wavelet coefficients to reduce the memory requirement in coding process. The 2D SCA is two dimensional data structure that has bit level information of the wavelet coefficients. The proposed algorithm performs the coding of the significance coefficients and coding of bit level information of wavelet coefficients at a time by using the 2D SCA. Experimental results show a better or similar performance of the proposed method when compared with conventional embedded wavelet coding algorithm. Especially, the proposed algorithm performs stably without image distortion at various b it rates with minimum memory usage by using the 2D SCA.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.29B no.11
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• pp.130-137
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• 1992

This paper presents the word recognition method using a neural-fuzzy pattern matching, in order to make a proper speech pattern for a spectrum sequence and to improve a recognition rate. In this method, a frequency variation is reduced by generating binary spectrum patterns through associative memory using a neural network, and a time variation is decreased by measuring the simillarity using a fuzzy pattern matching. For this method using binary spectrum patterns and logic algebraic operations to measure the simillarity, memory capacity and computation requirements are far less than those of DTW using a conventional distortion measure. To show the validity of the recognition performance for this method, word recognition experiments are carried out using 28 DDD city names and compared with DTW and a fuzzy pattern matching. The results show that our presented method is more excellent in the recognition performance than the other methods.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.22 no.4
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• pp.696-705
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• 1997

This paper presents an efficient adaptive predistortion technique compensating linear and nonlinear distortions caused by high-power amplifier (HPA) with memory in OFDM systems. The efficient adaptive data predistortion techniques proposed for compensation of HPA with memory in single carrier systems cannot be applied to OFDM systems since the possible input levels for HPA is infinite in OFDM systems. Also, previous adaptive predistortion techniques, based on Volterra series modeling, are not suitable for real-time implementation due to high computational burden and slow convergence rate. In the proposed approach, the memoryless HPA preceded by a linear filter in OFDM systems is modeled by the Wiener system which is then precompensated by the proposed adaptive predistorter with a minimum number of filter taps. An adaptive algorithm for adjusting the proposed adaptive predistorter is derived using the stochastic gradient method. It is demonstrated by computer simulation that the performance of OFDM system suffering from nonlinear distortion can be greatly improved by the proposed efficient adaptive predistorter using a small number of filter taps.

• Smart Structures and Systems
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• v.5 no.6
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• pp.645-662
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• 2009

Adaptive wings are capable of properly modifying their shape depending on the current aerodynamic conditions, in order to improve the overall performance of a flying vehicle. In this paper is presented the concept design of a small-scale compliant wing rib whose outline may be distorted in order to switch from an aerodynamic profile to another. The distortion loads are induced by shape memory alloy actuators placed within the frame of a wing section whose elastic response is predicted by the matrix method with beam formulation. Genetic optimization is used to find a wing rib structure (corresponding to the first airfoil) able to properly deforms itself when loaded by the SMA-induced forces, becoming as close as possible to the desired target shape (second airfoil). An experimental validation of the design procedure is also carried out with reference to a simplified structure layout.