• Journal of Communications and Networks
• /
• 제5권2호
• /
• pp.157-166
• /
• 2003

This paper deals with the problem of channel identification for Single Input Multiple Output (SIMO) slow fading channels using clustering algorithms. Due to the intrinsic memory of the discrete-time model of the channel, over short observation periods, the received data vectors of the SIMO model are spread in clusters because of the AWGN noise. Each cluster is practically centered around the ideal channel output labels without noise and the noisy received vectors are distributed according to a multivariate Gaussian distribution. Starting from the Markov SIMO channel model, simultaneous maximum ikelihood estimation of the input vector and the channel coefficients reduce to one of obtaining the values of this pair that minimizes the sum of the Euclidean norms between the received and the estimated output vectors. Viterbi algorithm can be used for this purpose provided the trellis diagram of the Markov model can be labeled with the noiseless channel outputs. The problem of identification of the ideal channel outputs, which is the focus of this paper, is then equivalent to designing a Vector Quantizer (VQ) from a training set corresponding to the observed noisy channel outputs. The Linde-Buzo-Gray (LBG)-type clustering algorithms [1] could be used to obtain the noiseless channel output labels from the noisy received vectors. One problem with the use of such algorithms for blind time-varying channel identification is the codebook initialization. This paper looks at two critical issues with regards to the use of VQ for channel identification. The first has to deal with the applicability of this technique in general; we present theoretical results for the conditions under which the technique may be applicable. The second aims at overcoming the codebook initialization problem by proposing a novel approach which attempts to make the first phase of the channel estimation faster than the classical codebook initialization methods. Sample simulation results are provided confirming the effectiveness of the proposed initialization technique.

• ETRI Journal
• /
• 제23권2호
• /
• pp.61-70
• /
• 2001

In this paper, we propose an efficient method for personal identification by analyzing iris patterns that have a high level of stability and distinctiveness. To improve the efficiency and accuracy of the proposed system, we present a new approach to making a feature vector compact and efficient by using wavelet transform, and two straightforward but efficient mechanisms for a competitive learning method such as a weight vector initialization and the winner selection. With all of these novel mechanisms, the experimental results showed that the proposed system could be used for personal identification in an efficient and effective manner.

• 한국정보통신학회논문지
• /
• 제11권9호
• /
• pp.1702-1708
• /
• 2007

Dragon 스트림 암호 알고리즘은 현재 ECRYPT 프로젝트의 일부인 eSTREAM에 참여하여 소프트웨어 분야(Profile 1)의 Phase 1, 2단계를 통과하여 Phase 3단계에 등록된 상태이다. Dragon은 기존의 스트림 암호와 달리 한 개의 워드(32비트)단위의 NLFSR(non-linear feedback shift register)을 사용하고, 128/256 비트의 key와 IV(Initialization Vector)를 입력받아 64비트의 키 수열을 생성하는 키 수열 발생기(Keystream Generator)이다. 본 논문에서는 Dragon 스트림 암호 알고리즘을 Altera사의 Quartus II툴을 이용하여 Cyclone III FPGA 소자(EP2C35F672I8)에 구현 및 타이밍 시뮬레이션을 하였고, 그 결과 111MHz에서 7.1Gbps의 처리량을 보였다.

• 제어로봇시스템학회:학술대회논문집
• /
• 제어로봇시스템학회 2002년도 ICCAS
• /
• pp.57.4-57
• /
• 2002

$\textbullet$ Image segmentation is an essential technique of image analysis. In spite of the traditional issues in contour initialization and boundary concavities, active contour models(snakes) are popular and known as successful methods for segmentation. $\textbullet$ We could find in experiment that snake using Gaussian External Force is fast in time but low in accuracy and snake using Gradient Vector Flow by Chenyang Xu and Jerry L. Prince is high in accuracy but slow in time. $\textbullet$ In this paper, we presented a new active contour model, GGF snake, for segmentation of endoscopic image. Proposed GGF snake made up for the defects of the traditional snakes in contour initialization and boundary...

• Journal of Multimedia Information System
• /
• 제7권2호
• /
• pp.165-174
• /
• 2020

This document outlines a new color image encryption technology development. After splitting the original image into 240-bit blocks and modifying the first block by an initialization vector, an improved Feistel circuit is applied, sponsored by a genetic crossover operator and then strong chaining between the encrypted block and the next clear block is attached to set up the confusion-diffusion and heighten the avalanche effect, which protects the system from any known attack. Simulations carried out on a large database of color images of different sizes and formats prove the robustness of such a system.

• 대한원격탐사학회:학술대회논문집
• /
• 대한원격탐사학회 2008년도 International Symposium on Remote Sensing
• /
• pp.216-219
• /
• 2008

It is necessary to study encryption for protection and safe transmission of the important information. Specially, the security in satellite data is also getting more and more important. This paper introduces DES and TDES algorithm, studies how to apply to satellite data with those algorithms and process of encryption and decryption for satellite data. Proposed encryption process in this paper will be utilized in satellite data for encryption in many satellites.

• 한국정보과학회:학술대회논문집
• /
• 한국정보과학회 2001년도 봄 학술발표논문집 Vol.28 No.1 (A)
• /
• pp.421-423
• /
• 2001

IPSec(IP Security)은 데이터가 공개적으로 전송되는 네트워크 데이터에 암호화와 인증, 무결성을 제공하기 위해 사용되는 프로토콜이다. IPSec 안에는 여러 프로토콜이 있는데, 그 중에 실제 패킷에 암호화와 인증, 무결성을 추가해 전달하기 위해서는 ESP(Encapsulation Security Payload)라는 프로토콜이 사용된다. 이 ESP(Encapsulation Security Payload)라는 프로토콜이 사용된다. 이 ESP는 패킷을 암호화하기 위해 DES-CBC 모드를 사용하는데, 여기에서 IV(Initialization Vector) 값이 쓰인다. 이 값은 패킷 복호화를 하기 위해 공개적으로 전달이 되기 때문에 중간에 공격자에 의해 공격 당할 위험이 많다. 본 논문에서는 IV 공격을 방지하기 위해 IV의 값을 해쉬 함수를 통해 한번 해슁을 한 다음에, IV 값을 안전하게 전달하는 방법을 제시하고자 한다.

• 한국전산유체공학회:학술대회논문집
• /
• 한국전산유체공학회 2008년도 춘계학술대회논문집
• /
• pp.568-571
• /
• 2008

The computation of moving interface by the level set method typically requires reinitializations of level set function. An inaccurate estimation of level set function ${\phi}$ results in incorrect free-surface capturing and thus errors such as mass gain/loss. Therefore, accurate and robust reinitialization process is essential to the free-surface flows. In the present paper, we pursue further development of the reinitialization process, which evaluates directly level set function ${\phi}$ using a normal vector in the interface without solving the re-distancing equation of hyperbolic type. The Taylor-Galerkin approximation and P1P1splitting FEM are adopted to discretize advection equation of the level set function and the Navier-Stokes equation, respectively. Advection equation of free surface and re-initialization process are validated with benchmark problems, i.e., a broken dam flow and time-reversed single vortex flow. The simulation results are in good agreement with the existing results.

• 대한기계학회논문집B
• /
• 제32권10호
• /
• pp.754-760
• /
• 2008

Computation of moving interface by the level set method typically requires the reinitialization of level set function. An inaccurate estimation of level set function $\phi$ results in incorrect free-surface capturing and thus errors such as mass gain/loss. Therefore, an accurate and robust reinitialization process is essential to the simulation of free-surface flows. In the present paper, we pursue further development of the reinitialization process, which evaluates level set function directly using a normal vector on the interface without solving there-distancing equation of hyperbolic type. The Taylor-Galerkin approximation and P1P1 splitting/SUPG (Streamline Upwind Petrov-Galerkin) FEM are adopted to discretize advection equation of the level set function and the incompressible Navier-Stokes equation, respectively. Advection equation and re-initialization process of free surface capturing are validated with benchmark problems, i.e., a broken dam flow and timereversed single vortex flow. The simulation results are in good agreement with the existing results.

• 한국정보과학회논문지:소프트웨어및응용
• /
• 제31권6호
• /
• pp.784-791
• /
• 2004

본 논문에서는 퍼지논리에 기초한 Fisherface 얼굴인식 방법의 확장을 다룬다. Fisherface 얼굴인식 방법은 주성분 분석 기법만을 이용하는 경우에 비해 조명의 방향, 얼굴의 포즈, 감정과 같은 변동에 대해 민감하지 않은 장점을 가지고 있다. 그러나, Fisherface 방법을 포함한 얼굴인식의 다양한 방법들은 입력 벡터가 한 클래스에 할당되어질 때 그 클래스에서 소속의 정도를 0 또는 1로서 나타낸다. 따라서 이러한 방법들은 얼굴영상들이 조명이나 보는 각도로 인해 변형이 생기는 경우에 인식률이 저하되는 문제가 있다. 본 논문에서는 PCA에 의해 변환된 특징벡터에 퍼지 소속도를 할당하는 것으로, 퍼지 소속도는 퍼지 kNN(k-Nearest Neighbor)으로부터 얻어진다. 실험 결과 ORL, Yale 얼굴 데이타베이스에서 기존의 인식방법 보다 향상된 인식 성능을 보임을 알 수 있었다.