• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2009.01a
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• pp.258-262
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• 2009

In this paper, we propose an effective memory reduction algorithm to reduce the amount of reference frame buffer and memory bandwidth in video encoder and decoder. In general video codecs, decoded previous frames should be stored and referred to reduce temporal redundancy. Recently, reference frames are recompressed for memory efficiency and bandwidth reduction between a main processor and external memory. However, these algorithms could hurt coding efficiency. Several algorithms have been proposed to reduce the amount of reference memory with minimum quality degradation. They still suffer from quality degradation with fixed-bit allocation. In this paper, we propose an adaptive block-based min-max quantization that considers local characteristics of image. In the proposed algorithm, basic process unit is $8{\times}8$ for memory alignment and apply an adaptive quantization to each $4{\times}4$ block for minimizing quality degradation. We found that the proposed algorithm could improve approximately 37.5% in coding efficiency, compared with an existing memory reduction algorithm, at the same memory reduction rate.

• IEIE Transactions on Smart Processing and Computing
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• v.5 no.5
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• pp.337-345
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• 2016

Recently, as the number of cores in computer systems has increased, the need for larger memory capacity has also increased. Unfortunately, dynamic random access memory (DRAM), popularly used as main memory for decades, now faces a scalability limitation. Phase change memory (PCM) is considered one of the strong alternatives to DRAM due to its advantages, such as high scalability, non-volatility, low idle power, and so on. However, since PCM suffers from short write endurance, direct use of PCM in main memory incurs a significant problem due to its short lifetime. To solve the lifetime limitation, many studies have focused on reducing the number of bit flips per write request. In this paper, we describe the PCM operating principles in detail and explore various bit flip reduction schemes. Also, we compare their performance in terms of bit reduction rate and lifetime improvement.

• JSTS:Journal of Semiconductor Technology and Science
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• v.14 no.6
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• pp.741-749
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• 2014

Low power double data rate 2 non-volatile memory (LPDDR2-NVM) has been deemed the standard interface to connect non-volatile memory devices such as phase-change memory (PCM) directly to the main memory bus. However, most of the previous literature does not consider or overlook this standard interface. In this paper, we propose address phase skipping by reforming the way of interfacing with LPDDR2-NVM. To verify effectiveness and functionality, we also develop a system-level prototype that includes our customized LPDDR2-NVM controller and commercial PCM devices. Extensive simulations and measurements demonstrate up to a 3.6% memory access time reduction for commercial PCM devices and a 31.7% reduction with optimistic parameters of the PCM research prototypes in industries.

• Journal of IKEEE
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• v.18 no.3
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• pp.392-397
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• 2014

In this paper, we propose a memory operation system architecture for memory latency penalty reduction in SIMT architecture based stream processor. The proposed architecture applied non-blocking cache architecture to reduce cache miss penalty generated by blocking cache architecture. We verified that the proposed memory operation architecture improve the performance of the stream processor by comparing processing performances of various algorithms. We measured the performance improvement rate that was improved in accordance with the ratio of memory instruction in each algorithm. As a result, we confirmed that the performance of stream processor improves up to minimum 8.2% and maximum 46.5%.

• Journal of the Institute of Electronics and Information Engineers
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• v.52 no.5
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• pp.66-73
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• 2015

IFFT is one of the key components in OFDM-based communication systems. In this paper, we propose a new memory efficient IFFT design method for OFDM-based communication systems, based on a mapping of three IFFT input signals which consist of modulated data, pilot and null signals. The proposed method focuses on reducing the memory size in the bit-reversal block which requires the largest number of memory cells in IFFT architectures. To reduce the memory size, we propose a selection mapping method based on decimation-in-time (DIT) algorithm. It is shown that the proposed method achieves a memory reduction of about 50% compared to conventional methods.

• Proceedings of the Korean Statistical Society Conference
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• 2000.11a
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• pp.23-26
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• 2000

It is noted that many econometric time series have long-memory properties. A long-memory process, or strongly dependent process, is characterized by hyperbolic decaying autocorrelations and unbounded spectral density at the origin. Since the long-memory property can be observed by data obtained from rather a long period, there is some possibility of parameter change in the process. In this paper, we consider the estimation of change-point when there is a change in the variance of a long-memory process. The estimator is based on some reasonable statistic and the consistency is shown using Taqqu's strong reduction theorem

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.13 no.1
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• pp.42-47
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• 2020

In OFDM-based very high-speed communication systems, FFT/IFFT processor should have several properties of low-area and low-power consumption as well as high throughput and low processing latency. Thus, radix-2k MDF (multipath delay feedback) architectures by adopting pipeline and parallel processing are suitable. In MDF architecture, the feedback memory which increases in proportion to the input signal word-length has a large area and power consumption. This paper presents a feedback memory size reduction method of radix-22 MDF IFFT processor for OFDM applications. The proposed method focuses on reducing the feedback memory size in the first two stages of MDF architectures since the first two stages occupy about 75% of the total feedback memory. In OFDM transmissions, IFFT input signals are composed of modulated data and pilot, null signals. In order to reduce the IFFT input word-length, the integer mapping which generates mapped data composed of two signed integer corresponding to modulated data and pilot/null signals is proposed. By simulation, it is shown that the proposed method has achieved a feedback memory reduction up to 39% compared to conventional approach.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.46 no.3
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• pp.68-74
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• 2009

In this paper, we propose an effective memory reduction algorithm to reduce the amount of reference frame buffer and memory bandwidth in video encoder and decoder. In general video codecs, decoded previous frames should be stored and referred to reduce temporal redundancy. Recently, reference frames are recompressed for memory efficiency and bandwidth reduction between a main processor and external memory. However, these algorithms could hurt coding efficiency. Several algorithms have been proposed to reduce the amount of reference memory with minimum quality degradation. They still suffer from quality degradation with fixed-bit allocation. In this paper, we propose an adaptive block-based min-max quantization that considers local characteristics of image. In the proposed algorithm, basic process unit is $8{\times}8$ for memory alignment and apply an adaptive quantization to each $4{\times}4$ block for minimizing quality degradation. We found that the proposed algorithm can obtain around 1.7% BD-bitrate gain and 0.03dB BD-PSNR gain, compared with the conventional fixed-bit min-max algorithm with 37.5% memory saving.

• Communications for Statistical Applications and Methods
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• v.31 no.2
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• pp.213-234
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• 2024

In recent decades, increasing research attention has been directed toward predicting the price of stocks in financial markets using deep learning methods. For instance, recurrent neural network (RNN) is known to be competitive for datasets with time-series data. Long short term memory (LSTM) further improves RNN by providing an alternative approach to the gradient loss problem. LSTM has its own advantage in predictive accuracy by retaining memory for a longer time. In this paper, we combine both supervised and unsupervised dimension reduction methods with LSTM to enhance the forecasting performance and refer to this as a dimension reduction based LSTM (DR-LSTM) approach. For a supervised dimension reduction method, we use methods such as sliced inverse regression (SIR), sparse SIR, and kernel SIR. Furthermore, principal component analysis (PCA), sparse PCA, and kernel PCA are used as unsupervised dimension reduction methods. Using datasets of real stock market index (S&P 500, STOXX Europe 600, and KOSPI), we present a comparative study on predictive accuracy between six DR-LSTM methods and time series modeling.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.46 no.1
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• pp.85-91
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• 2009

Recently, the LCD has high market share in TV market. The use of motion images in portable devices like DMB, PMP and Cell Phone is growing rapidly. One of the technique of enhancing the LCD's characteristic which is the slow response time. But, the technique requires a lot of memory usage, because of the requirement of frame memory. In this paper, we propose a reduction method for the frame memory that is required for LCD overdrive. Proposed overdrive architecture based on modified DWT-Inverse DWT and Color Conversion. The proposed architecture has a considerable PSNR. At once, it uses 50% of frame memory size and reduces 15% of frame memory size compare with previous architecture. The design was implemented using Xilinx Vertex4 and had 2172 Slice except Memory.