• The KIPS Transactions:PartC
• /
• v.12C no.1 s.97
• /
• pp.69-76
• /
• 2005

To effectively use limited resources in wireless cellular networks it is necessary to predict exactly the amount of resources required by handoff calls at a future time. In this paper we propose a method which predicts the amount of resources needed by handoff calls more accurately than the existing method based on Wiener processes. The existing method uses the current demands to predict future demands. Although this method is much simpler than using traffic information from neighbor cells, its prediction error increases as time elapses, leading to waste of wireless resources. By using an exponential parameter to decrease the magnitude of error over time, we show in simulation how to outperform the existing method in resource utilization as well as in prediction of resource demands.

• Proceedings of the Acoustical Society of Korea Conference
• /
• spring
• /
• pp.85-88
• /
• 2004

칼만/위너 필터 같은 기존의 음성향상 알고리즘은 잡음의 선험적 지식을 요구하고, 음성신호와 추정신호의 오차분산을 최소화하는데 중점을 두었다. 따라서, 잡음에 대한 통계적 추정에 오류가 있을 경우 결과에 악영향을 미칠 수 있다. 그러나 $H_\infty$ 필터는 잡음에 대한 어떠한 가정이나 선험적 지식을 요구하지 않는다. $H_\infty$ 필터는 최소상계(Upper Bound Least)를 적용하여 추정된 모든 신호들로부터 최소 에러 신호를 갖는 최상의 추정신호를 찾아내므로 칼만/위너 필터보다 잡음의 변화에 강인하다. 본 논문에서는 학습 신호로부터 은닉 마코프 모델의 파리미터를 추정한 후, 오염된 신호를 고정된 개수의 $H_\infty$ 필터를 통과시켜 각 출력에 가중된 합으로 향상된 음성 신호를 구한다. 음성의 통계적 특성을 이용하여 모델 파라미터를 추정하는 은닉 마코프 모델과 잡음의 변화에 강인한 $H_\infty$ 알고리즘을 사용해서, 다중 $H_\infty$필터에 의한 강인한 음성향상 방법을 제안하였다.

• Journal of Advanced Navigation Technology
• /
• v.13 no.3
• /
• pp.372-377
• /
• 2009

This paper evaluates the performance of three methods for predicting resources requested by mobile's calls and a call admission algorithm based on these predicting methods respectively in wireless networks. The first method is based on Wiener prediction model and the second method is based on the MMOSPRED algorithm and the third method is based on the neural network. The proposed call admission algorithm is based on prioritized handoff call in resource allocation. The resources for future handoff calls are therefore predicted and reserved in advance, and then new calls are admitted as long as the remaining resources are sufficient. We compare their performances in terms of prediction error, new call blocking and handoff dropping probabilities by simulation. Results show that the CAC based on Wiener prediction model performs favorably due to exact resources prediction.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.30 no.2A
• /
• pp.26-33
• /
• 2005

Exact prediction of resource demands for future calls enhances the efficiency of the limited resource utilization in resource reservation methods for potential calls in wireless IP networks. In this paper, we propose a LMS-Wiener resource(bandwidth) prediction for future handoff calls, and then an the proposed method is compared with an existing Wiener-based method in terms of prediction error through our simulations. In our simulations, we assume that handoff call arrivals follow a non-Poisson process and each handoff call has an non-exponentially distributed channel holdingtime in the cell, considering that handoff call arrival pattern is not Poisson distribution but non-Poisson for long periods of time in wireless picocellular IP networks. Simulation results show that the prediction error in the proposed method converges to the lower value while in an existing method increase as time is passed. Therefore we may conclude that the proposed method improves the efficiency of resource utilization by more exactly predicting resource demands for future handoff calls than an existing method.

• The Journal of the Acoustical Society of Korea
• /
• v.34 no.3
• /
• pp.227-233
• /
• 2015

In this paper, we propose music and voice separation using kernel sptectrogram models backfitting based on log-spectral amplitude estimator. The existing method separates sources based on the estimate of a desired objects by training MSE (Mean Square Error) designed Winer filter. We introduce rather clear music and voice signals with application of log-spectral amplitude estimator, instead of adaptation of MSE which has been treated as an existing method. Experimental results reveal that the proposed method shows higher performance than the existing methods.

• Proceedings of the KIEE Conference
• /
• 1997.07b
• /
• pp.437-440
• /
• 1997

제어공학에서 흔히 표준 모델이라고 불리우는 플랜트 모델은 여러 부 시스템이 서로 결합되어있는 복잡한 시스템을 단순화시킨 모델이다. 이 모델은 수학적으로 간략하게 표시된다는 장점 때문에 다변수 시스템의 최적 제어에 많이 쓰이고 있다. 그러나 이 모델은 수학적인 전개에는 편리하지만 물리적으로 판이하게 다른 신호군 즉, 외란 및 측정 잡음과 기준 입력 신호를 하나의 신호군으로 처리하는 약점이 있다. 실제로 이 구조로는 입력 추종 문제를 자유롭게 처리할 수 없는 경우가 있다. 본 연구에서는 이러한 문제를 개선하기 위하여 외란 및 측정 잡음과 기준 입력을 분리하여 처리할 수 있는 2자유도 제어기 구조를 제시하였다. 제어기 형태는 위너-호프 제어기로 주파수 영역에서 다 변수 시스템에 대한 최적 설계를 가능하게 한다.

• Journal of the Institute of Electronics and Information Engineers
• /
• v.50 no.8
• /
• pp.83-93
• /
• 2013

By comparing Wiener's MMSE on stochastic signal transmission with Shannon's mutual information first proved by C.E. Shannon in terms of information theory, connections between two approaches were investigated. What Wiener wanted to see in signal transmission in noisy channel is to try to capture fundamental limits for signal quality in signal estimation. On the other hands, Shannon was interested in finding fundamental limits of signal quantity that maximize the uncertainty in mutual information using the entropy concept in noisy channel. First concern of this paper is to show that in deriving limits of Shannon's point to point fundamental channel capacity, Shannon's mutual information obtained by exploiting MMSE combiner and Wiener filter's MMSE are interelated by integro-differential equantion. Then, At the meeting point of Wiener's MMSE and Shannon's mutual information the upper bound of spectral efficiency and the lower bound of energy efficiency were computed. Choosing a proper lattice-type code of a mod-${\Lambda}$AWGN channel model and MMSE estimation of ${\alpha}$ confirmed to lead to the fundamental Shannon capacity limits.

• Proceedings of the Korean Institute of Communication Sciences Conference
• /
• 2004.07a
• /
• pp.454-454
• /
• 2004

• Journal of the Korean Institute of Telematics and Electronics S
• /
• v.36S no.6
• /
• pp.45-56
• /
• 1999

This paper presents a method for designing an autopilot of the BTT missile using 2DOF Wiener-Hopf control technique to improve tracking performance. Linear controllers are designed based on the linearized models which are obtained from the nonlinear missile dynamic equations at various operating points. The gain scheduling technique is used to implement the final autopilot. A simulation on the flight of missiles is carried out through the use of 6DOF equation program including exact nonlinear equations of the missile and the variations of aerodynamic variables in order to check applicability of the suggested method in real situation.

• Journal of the Institute of Electronics Engineers of Korea TC
• /
• v.49 no.4
• /
• pp.9-17
• /
• 2012

In this paper, we show the memory effect of the high-power amplifiers for wied-band signals, present a compensation method for the nonlinearity combined with memory effect, and analyze its performance. For the modeling and the compensation of the nonlinear high-power amplifier with memory effect, we investigate the Volterra series model, the Wiener model, and the Hammerstein model. As a compensator scheme, we propose a digital feedforward technique. Compared to analog feed-forward scheme, the proposed scheme has better stability and adaptability to the environmental changes. It has a simpler structure than the conventional digital nonlinear compensation schemes. The result of computer simulations using ADS of the Agilent shows that spectral re-growth is suppressed by more than 20 dB, which amounts to at least 10 dB back-off. Considering the compensation performance, implementation complexity, and convergence rate, we could conclude the Wiener model is most suitable for the proposed scheme.