• 대한원격탐사학회지
• /
• 제22권2호
• /
• pp.101-110
• /
• 2006

본 연구에서는 항공 관측으로 얻어진 다중분광영상과 LIDAR (LIght Detection And Ranging) 자료를 이용하여 농업지역의 토지피복 분류 정도를 분석하였다. 다중분광영상은 녹색, 적색, 근적외역의 3분광으로 이루어져 있다. LIDAR 벡터 자료로부터 최초 반사강도 영상과 최초 반사 표고 자료와 최후 반사의 지상 표고 자료의 차이로 산출된 식생 높이 영상이 얻어졌다. 토지피복 분류 방법은 최대우도법을 사용했으며, 다중분광영상의 3밴드 영상 LIDAR의 반사강도 영상, 식생 높이 영상을 이용하였다. 모든 영상을 이용한 토지피복 분류의 전체 정도는 85.6%로 다중분광영상만을 이용한 정도보다 10%이상 향상되었다. 여러 농작물간의 높이의 차이, 수목과 농작물 높이의 차이와 LIDAR 반사강도 차이로 인하여 다중분광영상과 LIDAR 영상을 사용한 토지피복 분류의 정도가 향상되었다.

• Asian-Australasian Journal of Animal Sciences
• /
• 제18권8호
• /
• pp.1088-1097
• /
• 2005

Main objectives of this study were to investigate accuracy, bias and power of linear and threshold model segregation analysis methods for detection of major genes in categorical traits in farm animals. Maximum Likelihood Linear Model (MLLM), Bayesian Linear Model (BALM) and Bayesian Threshold Model (BATM) were applied to simulated data on normal, categorical and binary scales as well as to disease data in pigs. Simulated data on the underlying normally distributed liability (NDL) were used to create categorical and binary data. MLLM method was applied to data on all scales (Normal, categorical and binary) and BATM method was developed and applied only to binary data. The MLLM analyses underestimated parameters for binary as well as categorical traits compared to normal traits; with the bias being very severe for binary traits. The accuracy of major gene and polygene parameter estimates was also very low for binary data compared with those for categorical data; the later gave results similar to normal data. When disease incidence (on binary scale) is close to 50%, segregation analysis has more accuracy and lesser bias, compared to diseases with rare incidences. NDL data were always better than categorical data. Under the MLLM method, the test statistics for categorical and binary data were consistently unusually very high (while the opposite is expected due to loss of information in categorical data), indicating high false discovery rates of major genes if linear models are applied to categorical traits. With Bayesian segregation analysis, 95% highest probability density regions of major gene variances were checked if they included the value of zero (boundary parameter); by nature of this difference between likelihood and Bayesian approaches, the Bayesian methods are likely to be more reliable for categorical data. The BATM segregation analysis of binary data also showed a significant advantage over MLLM in terms of higher accuracy. Based on the results, threshold models are recommended when the trait distributions are discontinuous. Further, segregation analysis could be used in an initial scan of the data for evidence of major genes before embarking on molecular genome mapping.

• 한국정보통신학회:학술대회논문집
• /
• 한국해양정보통신학회 2007년도 추계종합학술대회
• /
• pp.83-86
• /
• 2007

In the blind Maximum-likelihood (ML) detection for Orthogonal Space-Time Block Codes (OSTBC), the problem of ambiguity in determining the symbols has been a great concern. A solution to this problem is to apply semi-blind ML detection, i.e., the blind ML decoding with pilot symbols or training sequence. In order to increase the performance, the number of pilot symbols or length of training sequence should be increased. Unfortunately, this leads to a significant decrease in system spectral efficiency. This work presents an approach to resolve the aforementioned issue by introducing a new method for constructing transmitted information symbol. Thus, by transmitting information symbols drawn from different modulation constellation, the ambiguity can be easily eliminated in blind detection. Also, computer simulations are implemented to verify the performance of the proposed approach.

• 한국통신학회논문지
• /
• 제22권1호
• /
• pp.30-39
• /
• 1997

본 논문은 CDMA 셀룰라 역방향 접속 시스템의 성능개선을 위하여 이중직교 신호에 대한 다중심볼 검파방식을 제안하고, 이에 대한 성능해석과 컴퓨터 모의실험을 수행한다. 이 방식은 기존의 심볼단위 비동기 검파대신 복잡도를 줄인 근사 MLSE에 의해 다중심볼로 구성된 복조 데이터와 채널을 동시에 예측한다. 이 방식은 또한 주어진 심볼의 워드수 M에 대해 관측하는 다중심볼 길이 N을 적절히 선택할 때 채널의 예측이 없이도 이상적인 동기검파 방식에 근접한 오류성능을 얻게 해준다. 특히 매우 의미 있는 사항은 이 방식을 CDMA 역방향 접속 시스템에 적용할 때 요구되는 평균 비트당 신호대 잡은 전력비 ${\gamma}_{b}$를 약 1.4dB정도 줄일 수 있어 38% 정도의 용량이 증가된다.

• 한국통신학회논문지
• /
• 제33권11C호
• /
• pp.932-939
• /
• 2008

공간 다중화 방식의 MIMO(Multiple-Input Multiple-Output) 시스템에서 MLD(Maximum-Likelihood Detector)는 최적의 성능을 보이지만, 그 복잡성이 상당히 큰 단점이 있다. 이를 보완하기 위해 여러 가지 기법들이 제안되었으며, Lattice-reduction(LR) 검출기 또한 MIMO 시스템의 성능을 개선하기 위해 제안되었다. 본 논문에서는 확장된 잡음분산 행렬을 이용해 rounding operation 과정에서 발생하는 양자화 오류를 이용해 송신 신호 벡터에 근접한 candidate symbol set을 찾고, 여기서 Semidefinite Relaxation을 이용해 최대 우도 symbol을 검출한다. 그러나 그 복잡도는 MLD의 복잡도 보다 현저히 작고, LR 검출기의 복잡도에 근접한다.

• Journal of Communications and Networks
• /
• 제5권1호
• /
• pp.33-42
• /
• 2003

In this paper a two-stage maximum-likelihood (ML) detection structure for group detection in DS/CDMA systems is presented. The first stage of the receiver is a linear filter, aimed at suppressing the effect of the unwanted (i.e., out-of-grout) users' signals, while the second stage is a non-linear block, implementing a ML detection rule on the set of desired users signals. As to the linear stage, we consider both the decorrelating and the minimum mean square error approaches. Interestingly, the proposed detection structure turns out to be a generalization of Varanasi's group detector, to which it reduces when the system is synchronous, the signatures are linerly independent and the first stage of the receiver is a decorrelator. The issue of blind adaptive receiver implementation is also considered, and implementations of the proposed receiver based on the LMS algorithm, the RLS algorithm and subspace-tracking algorithms are presented. These adaptive receivers do not rely on any knowledge on the out-of group users' signals, and are thus particularly suited for rejection of out-of-cell interference in the base station. Simulation results confirm that the proposed structure achieves very satisfactory performance in comparison with previously derived receivers, as well as that the proposed blind adaptive algorithms achieve satisfactory performance.

• Journal of Communications and Networks
• /
• 제12권5호
• /
• pp.475-479
• /
• 2010

The clipping value, defined as the log-likelihood ratio (LLR) in the case wherein all the list of candidates have the same binary value, is investigated, and an effective method to estimate it is presented for iterative tree search detection. The basic principle behind the method is that the clipping value of a channel bit is equal to the LLR of the maximum probability of correct decision of the bit to the corresponding probability of erroneous decision. In conjunction with multilevel bit mappings, the clipping value can be calculated with the parameters of the number of transmit antennas, $N_t$; number of bits per constellation point, $M_c$; and variance of the channel noise, $\sigma^2$, per real dimension in the Rayleigh fading channel. Analyses and simulations show that the bit error performance of the proposed method is better than that of the conventional fixed-value method.

• 대한전기학회:학술대회논문집
• /
• 대한전기학회 2008년도 학술대회 논문집 정보 및 제어부문
• /
• pp.113-114
• /
• 2008

In this paper, binary pulse-position modulation (2PPM) time-hoping (TH) ultra-wideband (UWB) system is applied to multiple input multiple output (MIMO) system using vertical bell lab layered space-time (V-BLAST) structure to achieve high-data-rate communications. This UWB-MIMO system and its receivers are analyzed, and its BER performances are evaluated. In the receiver, various MIMO detection algorithms such as zero-forcing (ZF), ZF-ordered successive interference cancellation (OSIC), minimum-mean-square-error (MMSE), MMSE-OSIC and maximum likelihood (ML) are comparatively studied.

• 대한전기학회:학술대회논문집
• /
• 대한전기학회 2003년도 하계학술대회 논문집 D
• /
• pp.2289-2291
• /
• 2003

NLPCA(Nonlinear Principal Component Analysis is a novel technique for multivariate data analysis, similar to the well-known method of principal component analysis. NLPCA can be implemented by a feedforward neural network called AANN (AutoAssociative Neural Network) which performs the identity mapping. In this work, a sensor fault detection system based on NLPCA and Maximum Likelihood Estimation scheme is presented. To verify its applicability, simulation study on the data supplied from Saemangeum measurement stations is executed.

• Journal of Information Processing Systems
• /
• 제13권4호
• /
• pp.1029-1042
• /
• 2017

A joint channel estimation and data detection technique for a multiple input multiple output (MIMO) wireless communication system is proposed. It combines the least square (LS) training based channel estimation (TBCE) scheme with sphere decoding. In this new approach, channel estimation is enhanced with the help of blind symbols, which are selected based on their correctness. The correctness is determined via sphere decoding. The performance of the new scheme is studied through simulation in terms of the bit error rate (BER). The results show that the proposed channel estimation has comparable performance and better computational complexity over the existing semi-blind channel estimation (SBCE) method.