• Journal of Electrical Engineering and information Science
• /
• 제3권2호
• /
• pp.211-221
• /
• 1998

It is becoming apparent that stereo matching algorithms need much information from high level cognitive processes. Otherwise, conventional algorithms based on bottom-up control alone are susceptible to local minima. We introduce a system that consists of two levels. A lower level, using a usual matching method, is based upon the local neighborhood and a second level, that can integrate the partial information, is aimed at contextual matching. Conceptually, the introduction of bottom-up and top-down feedback loop to the usual matching algorithm improves the overall performance. For this purpose, we model the image attributes using a Markov random field (MRF) and thereupon derive a maximum a posteriori (MAP) estimate. The energy equation, corresponding to the estimate, efficiently represents the natural constraints such as occlusion and the partial informations from the other levels. In addition to recognition, we derive a training method that can determine the system informations from the other levels. In addition to recognition, we derive a training method that can determine the system parameters automatically. As an experiment, we test the algorithms using random dot stereograms (RDS) as well as natural scenes. It is proven that the overall recognition error is drastically reduced by the introduction of contextual matching.

• KIEE International Transaction on Systems and Control
• /
• 제2D권2호
• /
• pp.97-107
• /
• 2002

In this paper, we propose the concept of orthonormalized compressed measurement for the stability analysis of discrete linear time-varying Kalman filters. Unlike previous studies that deal with the homogeneous portion of Kalman filters, the proposed Lyapunov method directly deals with the stochastically-driven system. The orthonorrmalized compressed measurement provides information on the a priori state estimate of the Kalman filter at the k-th step that is propagated from the a posteriori state estimate at the previous block of time. Since the complex multiple-step propagations of a candidate Lyapunov function with process and measurement noises can be simplified to a one-step Lyapunov propagation by the orthonormalized compressed measurement, a stochastic radius of attraction can be derived that would be impractically difficult to obtain by the conventional multiple-step Lyapunov method.

• International Journal of Precision Engineering and Manufacturing
• /
• 제5권4호
• /
• pp.61-68
• /
• 2004

Necessity to address engineering system uncertainties in design processes has long been acknowledged. To obtain quality of product, a safety factor is traditionally used by many design engineers due to its easy of use and comprehension. However, the safety factor approach often yields either conservative or unreliable designs, since it ignores the type of probability distribution and the mechanism of uncertainty propagation from the input to the output. For a consistent reliability-based design, two fundamental issues must be investigated thoroughly. First, the design-decision process that clearly identifies a mechanism of uncertainty propagation under system uncertainties needs to be developed, which must be an efficient and accurate process. To identify the mechanism more effectively, an adaptive probability analysis is proposed by adaptively setting probability levels through a posteriori error estimation. The second is to develop the design process that not only yields a high quality design but also a cost-effective optimum design from manufacturing point of view. As a result, a response surface methodology is specially developed for RBDO, thus enhancing numerical challenges of efficiency and complicatedness. Side crashworthiness application is used to demonstrate the integrated design process for product and manufacturing process design.

• Journal of Communications and Networks
• /
• 제5권2호
• /
• pp.135-140
• /
• 2003

In this paper, we investigate the error performance of a serially concatenated system using a nonrecursive convolutional code as the outer code and a recursive QPSK space-time trellis code as the inner code on quasi-static and rapid Rayleigh fading channels. At the receiver, we consider iterative decoding based on the maximum a posteriori (MAP) algorithm. The performance is evaluated by means of computer simulations and it is shown that better error performance can be obtained by using low complexity outer and/or inner codes and the Euclidean distance criterion based recursive space-time inner codes. We also obtain new systems with large number of trasmit and/or receive antennas providing good error performance.

• Transactions on Control, Automation and Systems Engineering
• /
• 제1권1호
• /
• pp.75-86
• /
• 1999

An air-data estimator for generic air-breathing hypersonic vehicles (AHSVs) is developed and demonstrated with an example vehicle configuration. The AHSV air-data estimation strategy emphasized improvement of the angle of attack estimate accuracy to a degree necessitated by the stringent operational requirements of the air-breathing propulsion. the resulting estimation problem involves highly nonlinear diffusion process (propagation); consequently, significant distortion of a posteriori conditional density is suspected. A simulation based statistical analysis tool is developed to characterize the nonlinear diffusion process. The statistical analysis results indicate that the diffusion process preserves the symmetry and unimodality of initial probability density shape state variables, and provide the basis for applicability of an Extended Kalman Filter (EKF). An EKF is designed for the AHSV air-data system and the air data estimation capabilities are demonstrated.

• International Journal of Computer Science & Network Security
• /
• 제22권12호
• /
• pp.51-56
• /
• 2022

In space based constellation network, users are allowed to enter or leave the network arbitrarily. Hence, the number, identities and transmitted data of active users vary with time and have considerable impacts on the receiver's performance. The so-called problem of multiuser detection means identifying the identity of each active user and detecting the data transmitted by each active user. Traditional methods assume that the number of active users is equal to the maximum number of users that the network can hold. The model of traditional methods are simple and the performance are suboptimal. In this paper a Maximum A Posteriori Probability (MAP) based multiuser detection method is proposed. The proposed method models the activity state of users as Markov chain and transforms multiuser detection into searching optimal path in grid map with BCJR algorithm. Simulation results indicate that the proposed method obtains 2.6dB and 1dB E_b/N₀ gains respectively when activity detection error rate and symbol error rate reach 10^-3, comparing with reference methods.

• 전기의세계
• /
• 제22권3호
• /
• pp.49-62
• /
• 1973

An algorithm for the state estimation and identification of multivariable nonlinear systems with noisy nonlinear observation has been investigated on the basis of the multidimensional Hermitian expansion for the a posteriori probability densities of the predicted observation, the predicted state and the observation conditioned by the state. A new approach for construction of this sequential nonlinear estimator, retaining up to the second order term of the observation error, has been developed, along with the approximation of nonlinear system functions, truncating at the second term. The estimation of the unknown parameters has been established by extending the state estimation technique, regarding the parameters as another state variables. The results of investigation indicate the feasibility of the schemes presented in this paper.

• 전자공학회논문지CI
• /
• 제48권4호
• /
• pp.21-26
• /
• 2011

특징 순위 방법은 데이터에 대한 정보와 관련된 특징을 구별하는데 유용하게 사용된다. 본 논문에서는 혈소판으로부터 측정된 라만 스펙트럼에서 퇴행성 뇌신경질환과 혈관성 인지증의 분류에 특징 순위를 이용하는 방법을 제안하였다. 퇴행성 뇌신경 질환인 알츠하이머병(Alzheimer's disease)과 파킨슨병(Parkinson's disease) 그리고 혈관성 인지증(vascular dementia)을 유도한 실험용 쥐의 혈소판에서 측정한 스펙트럼은 가우시안 모델을 이용한 커브 피팅으로 노이즈를 제거하고 로컬 최저점에 선형 보간법(linear interpolation)으로 배경 잡음을 제거한다. 전처리 과정을 수행한 스펙트럼에서 분류정확도와 계산복잡도를 개선하기 위해 특징 순위 방법을 이용하여 주요 특징을 선택하였다. 선택된 특징들은 PCA(principal component analysis) 방법으로 변환하여 주성분의 수를 변화시키며 MAP(maximum a posteriori)으로 분류하고 전체 특징을 사용한 경우의 분류 결과와 비교하였다. 실험 결과에서 제안한 방법을 적용한 모든 실험에서 분류 시스템의 계산복잡도를 현저하게 감소시키고 분류정확도는 부분적으로 증가하였다. 특히 파킨슨병과 정상을 분류하는 실험에서 제안한 방법이 전체 특징을 사용한 경우보다 모든 주성분의 수에서 분류정확도가 높았으며 평균 1.7 %의 성능이 향상되었다. 이 결과에서 분류정확도와 계산복잡도의 개선을 고려하면 제안한 방법이 혈소판 라만 스펙트럼에서 퇴행성 뇌신경질환과 혈관성 인지증의 분류 시스템에 효율적으로 사용될 수 있음을 확인하였다.

• The Journal of the Acoustical Society of Korea
• /
• 제23권3E호
• /
• pp.85-90
• /
• 2004

This paper presents two kinds of new approaches, one of which is concerned with recognition of emotional speech such as anger, happiness, normal, sadness, or surprise. The other is concerned with emotion recognition in speech. For the proposed speech recognition system handling human speech with emotional states, total nine kinds of prosodic features were first extracted and then given to prosodic identifier. In evaluation, the recognition results on emotional speech showed that the rates using proposed method increased more greatly than the existing speech recognizer. For recognition of emotion, on the other hands, four kinds of prosodic parameters such as pitch, energy, and their derivatives were proposed, that were then trained by discrete duration continuous hidden Markov models(DDCHMM) for recognition. In this approach, the emotional models were adapted by specific speaker's speech, using maximum a posteriori(MAP) estimation. In evaluation, the recognition results on emotional states showed that the rates on the vocal emotions gradually increased with an increase of adaptation sample number.

• 전자공학회논문지S
• /
• 제35S권4호
• /
• pp.105-117
• /
• 1998

In this paper, the general formula of disparity estimation based on Bayesian Maximum A Posteriori (MAP) algorithm is derived and implemented with simplified probabilistic models. The probabilistic models are independence and similarity among the neighboring disparities in the configuration.The formula is the generalized probabilistic diffusion equation based on Bayesian model, and can be implemented into the some different forms corresponding to the probabilistic models in the disparity neighborhood system or configuration. And, we proposed new probabilistic models in order to simplify the joint probability distribution of disparities in the configuration. According to the experimental results, the proposed algorithm outperformed the other ones, such as sum of swuared difference(SSD) based algorithm and Scharstein's method. We canconclude that the derived formular generalizes the probabilistic diffusion based on Bayesian MAP algorithm for disparity estimation, and the propsoed probabilistic models are reasonable and approximate the pure joint probability distribution very well with decreasing the computations to 0.01% of the generalized formula.