• Journal of the Korean Institute of Telematics and Electronics
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• v.12 no.2
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• pp.1-10
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• 1975

This paper presents an adaptive data compression algorithm for video data. The coling complexity due to the high correlation in the given data sequence is alleviated by coding the difference data, sequence rather than the data sequence itself. The adaptation to the nonstationary statistics of the data is confined within a code set, which consists of two constant length cades and six modified Shannon.Fano codes. lt is assumed that the probability distributions of tile difference data sequence and of the data entropy are Laplacian and Gaussion, respectively. The adaptive coding performance is compared for two code selection criteria: entropy and $P_r$[difference value=0]=$P_0$. It is shown that data compression ratio 2 : 1 is achievable with the adaptive coding. The gain by the adaptive coding over the fixed coding is shown to be about 10% in compression ratio and 15% in code efficiency. In addition, $P_0$ is found to he not only a convenient criterion for code selection, but also such efficient a parameter as to perform almost like entropy.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.30 no.4C
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• pp.191-199
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• 2005

Space-time turbo codes have been studied extensively as a powerful and bandwidth efficient error correction code over the wireless communication environment. In this paper, the efficient algorithm for decoding space-time turbo codes is proposed. The proposed method reduces the computational complexity by approximating a prior information for a iterative decoder. The performance of space-time turbo codes is also analyzed by using the fixed point implementation and the efficient method for approximating the Log-MAP algorithm is proposed. It is shown that the BER performance of the proposed method is close to that of the Log-MAP algorithm.

• Journal of Communications and Networks
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• v.16 no.5
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• pp.512-522
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• 2014

This paper proposes fast millimeter-wave (mm-wave) beam training protocols with receive beamforming. Both IEEE standards and the academic literature have generally considered beam training protocols involving exhaustive search over all possible beam directions for both the beamforming initiator and responder. However, this operation requires a long time (and thus overhead) when the beamwidth is quite narrow such as for mm-wave beams ($1^{\circ}$ in the worst case). To alleviate this problem, we propose two types of adaptive beam training protocols for fixed and adaptive modulation, respectively, which take into account the unique propagation characteristics of millimeter waves. For fixed modulation, the proposed protocol allows for interactive beam training, stopping the search when a local maximum of the power angular spectrum is found that is sufficient to support the chosen modulation/coding scheme. We furthermore suggest approaches to prioritize certain directions determined from the propagation geometry, long-term statistics, etc. For adaptive modulation, the proposed protocol uses iterative multi-level beam training concepts for fast link configuration that provide an exhaustive search with significantly lower complexity. Our simulation results verify that the proposed protocol performs better than traditional exhaustive search in terms of the link configuration speed for mobile wireless service applications.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.19 no.1
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• pp.111-119
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• 1994

In this paper we propose a reversible image coding methods with progressive build-up function by bit-plane of multi-lavel image. Firstly, the differencial conversion is applied to reduce the entropy of source images. Then the bit-plane sequences of converted images are coded by means of the newly designed VFRL(Variable to Fixed Run-Llength) code and the RDHC(Run-length Dynamic Huffman Coding). We aim to the simple construction to reduce the complexity. The computer simulated results show that the proposed methods are very effective to the multi-level digital images. For "GIRL" and "COUPLE" of 1EEE monochromatic standard images, the compressibility are superior to the results obtained by the well-known universal codes.own universal codes.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.36 no.6C
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• pp.337-342
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• 2011

In 2009, polar codes, proposed by Arikan, are theoretically proven codes to achieve capacity with acceptable encoding and decoding complexity. Currently, polar codes using channel polarization phenomenon are studied in security and data compression fields etc. In this paper, we consider the practical communication system and propose the construction method of polar codes with finite length and fixed code rate. Also, we show the outstanding performance and corresponding construction method of polar codes found by heuristic simulation.

• ETRI Journal
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• v.33 no.5
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• pp.689-694
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• 2011

In this paper, we study scheduling schemes for two-user two-way wireless relaying systems. Two transmission modes are considered: point-to-point direct transmission and two-way amplify-and-forward relaying. An optimal scheduling scheme that opportunistically selects the best transmission mode for each user is proposed to minimize the sum bit error rate (BER). The performance lower bound of the optimal scheduling scheme is analyzed, and closed-form expression of the lower-bound BER is derived. However, for optimal scheduling, the scheduler requires the knowledge of channel state information (CSI) of all links. To reduce the feedback information of CSI, we also propose a suboptimal scheduling scheme that selects the transmission mode using only the CSI of two direct links. Simulation results show that there are 4 dB to 8 dB gains for the proposed optimal and suboptimal schemes over the fixed direct transmission and fixed two-way relayed transmission scheme. The performance gap between the optimal and suboptimal scheduling schemes is small, which implies a good trade-off between implementation complexity and system performance.

• Proceedings of the KIEE Conference
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• 1996.07b
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• pp.1295-1297
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• 1996

CCITT G.721, G.723 standard ADPCM algorithm is implemented by using TI's fixed point DSP start kit (DSK). ADPCM can be implemented on a various rates, such as 16K, 24K, 32K and 40K. The ADPCM is sample based compression technique and its complexity is not so high as the other speech compression techniques such as CELP, VSELP and GSM, etc. ADPCM is widely applicable to most of the low cost speech compression application and they are tapeless answering machine, simultaneous voice and fax modem, digital phone, etc. TMS320C50 DSP is a low cost fixed point DSP chip and C50 DSK system has an AIC (analog interface chip) which operates as a single chip A/D and D/A converter with 14 bit resolution, C50 DSP chip with on-chip memory of 10K and RS232C interface module. ADPCM C code is compiled by TI C50 C-compiler and implemented on the DSK on-chip memory. Speech signal input is converted into 14 bit linear PCM data and encoded into ADPCM data and the data is sent to PC through RS232C. The ADPCM data on PC is received by the DSK through RS232C and then decoded to generate the 14 bit linear PCM data and converted into the speech signal. The DSK system has audio in/out jack and we can input and out the speech signal.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.6 no.1
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• pp.426-445
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• 2012

Conventional rate control (RC) schemes for H.264 video coding usually regulate output bit rate to match channel bandwidth by adjusting quantization parameter (QP) at fixed full frame rate, and the passive frame skipping to avoid buffer overflow usually occurs when scene changes or high motions exist in video sequences especially at low bit rate, which degrades spatial-temporal quality and causes jerky effect. In this paper, an active content adaptive frame skipping scheme is proposed instead of passive methods, which skips subjectively trivial frames by structural similarity (SSIM) measurement between the original frame and the interpolated frame via motion vector (MV) copy scheme. The saved bits from skipped frames are allocated to coded key ones to enhance their spatial quality, and the skipped frames are well recovered based on MV copy scheme from adjacent key ones at the decoder side to maintain constant frame rate. Experimental results show that the proposed active SSIM-based frameskip scheme acquires better and more consistent spatial-temporal quality both in objective (PSNR) and subjective (SSIM) sense with low complexity compared to classic fixed frame rate control method JVT-G012 and prior objective metric based frameskip method.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.15 no.2
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• pp.13-22
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• 2005

To improve the anomaly IDS using system calls, this study focuses on Neural Networks Learning using the Soundex algorithm which is designed to change feature selection and variable length data into a fixed length learning pattern. That is, by changing variable length sequential system call data into a fixed length behavior pattern using the Soundex algorithm, this study conducted neural networks learning by using a backpropagation algorithm with fuzzy membership function. The back-propagation neural networks and Neuro-Fuzzy technique are applied for anomaly intrusion detection of system calls using Sendmail Data of UNM to demonstrate its aspect of he complexity of time, space and MDL performance.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2020.11a
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• pp.252-255
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• 2020

Unsupervised deep learning methods have shown impressive results for the challenging monocular depth estimation task, a field of study that has gained attention in recent years. A common approach for this task is to train a deep convolutional neural network (DCNN) via an image synthesis sub-task, where additional views are utilized during training to minimize a photometric reconstruction error. Previous unsupervised depth estimation networks are trained within a fixed depth estimation range, irrespective of its possible range for a given image, leading to suboptimal estimates. To overcome this suboptimal limitation, we first propose an unsupervised adaptive depth estimation method guided by minimum and maximum (min-max) depth priors for a given input image. The incorporation of min-max depth priors can drastically reduce the depth estimation complexity and produce depth estimates with higher accuracy. Moreover, we propose a novel network architecture for adaptive depth estimation, called the AdaMM-DepthNet, which adopts the min-max depth estimation in its front side. Intensive experimental results demonstrate that the adaptive depth estimation can significantly boost up the accuracy with a fewer number of parameters over the conventional approaches with a fixed minimum and maximum depth range.