Earticle

A new actuating mechanism suitable for a micro positioning device is developed using piezo-electric elements. The actuator can make a step movement of 0.5 .mu. m up to 3.5 .mu. m. The step size can be adjusted on demand. By repeating this step action, long distance movement is achieved. Precise positioning can be obtained by combining the coarse motion with the maximum step size and fine motion. Two types of fine motion have been proposed for a driving method. Firstly, feedback control bases on PID is applied. The experimental results for the two method are presented.

Firstly the Decomposition Least Mean (D‐LMS) algorithm is analyzed deeply in theoretical, then a variable step size D‐LMS algorithm is proposed. By using the MATLAB based simulation model, the system identification results of the stable step size D‐LMS algorithm and the ones of the variable step‐size D‐LMS algorithm are both obtained. The simulation results show that compared with the stable step size D‐LMS algorithm, this variable step‐size D‐LMS algorithm based on wavelet transform has the better convergence ability and tracing ability, but the less state errors.

본 논문에서는 비선형 전달 특성을 갖는 채널에서 발생되는 부호간 간섭의 영향을 최소화시킬 수 있는 S-MMA (Sliced-Multi Modulus Algorithm) 등화 알고리즘에 가변 스텝 크기를 적용하여 등화 성능을 개선시킬 수 있는 알고리즘을 제안한다. 기존의 MMA 알고리즘에서 정상 상태에서 등화 성능과 misadjustment를 개선하기 위하여 S-MMA가 등장하였으며, 이들 알고리즘에서는 오차 신호의 크기에 따른 고정 스텝 크기로 적응하기 때문에 성능 개선에 한계가 있다. 이와 같은 문제를 극복하기 위하여 제안 알고리즘에서는 오차 신호의 크기에 비례하는 가변 스텝 크기를 적용하며, 개선 효과를 보이기 위하여 컴퓨터 시뮬레이션을 수행하였으며, 시뮬레이션 결과 제안 VSS S-MMA 알고리즘이 기존 S-MMA보다 등화 성능이 우월함을 확인하였다.

This paper proposes the improving the equalization performance using the variable step size in the S-MMA (Sliced-Multi Modulus Algorithm) equalization algorithm in order to minimize the effect of intersymbol interference which occurs at the nonlinear transfer function of communication channel. The S-MMA were showned for the improving the steady state equalization performance and misadjustment compared to the MMA present algorithm, this two algorithm has a limitation of performance improvement due to the adapting the fixed step size according to the error signal amplitude. In order to solving the abovemensioned problem, the proposed algorithm was adopting the variable step size proportional to the error signal amplitude and the computer simulation was performed for showing the performance improving. As a result of simulation, the proposed VSS S-MMA algorithm has more superior equalization performance compared to the present S-MMA.

Elimination of noise from the signal is the major task in signal processing applications. Wiener filter removes noise efficiently but it requires large number of computations and it was updated with speed issue with adaptive filter. Adaptive filter has several algorithms to remove noise from the signal. This paper performs cancellation of noise from the signal using wiener filter and adaptive filter algorithms namely LMS, NLMS and RLS algorithms in real time environment. All these methods are compared using several parameters like step size, mean and variance of noise, mean square error, signal to noise ratio, speed, no. of. Iterations etc. In the existence work, the authors have compared the performance of the wiener filter & LMS algorithm in real time environment with sinusoidal input. This paper is extended by comparing different adaptive filter algorithms with the input taken in real time environment. It is observed that RLS algorithm performs noise cancellation better than all other algorithms. But it has high degree of complexity & cost while NLMS algorithm has moderate speed of performance and it is quietly chosen for several applications.

Compressed sensing is a new signal sampling theory that fully makes use of signal’s sparsity or compressibility. The theory shows that, the acquisition of a small amount of the sparse or compressible signal value can be used for exact signal reconstruction. Based on the study and summarization of the existing reconstruction algorithms, this paper proposes a novel blocking variable step size forward-backward pursuit (BVSSFBP). This paper proposed variable step size forward-backward pursuit algorithm by introducing the concept of sparse phase and variable step size to deal with different situations. The algorithm also divides two-dimensional image into blocks, in order to reduce the scale of observation matrix during single processing, reduce the single processing speed and the overall running time. Experimental results show BVSSFBP algorithm can obtain better reconstructed image quality.

본 논문은 가변 스텝 크기를 가지는 MSAG-GMMA(modified Stop-and-Go generalized multi modulus algorithm) 적응 블라인드 등화 알고리즘의 성능 분석에 관한 것이다. 제안한 알고리즘은 등화 계수 갱신 식에서 고정 스텝 크기에 결정지향 알고리즘의 오차신호의 크기를 곱하여 오차크기에 따라서 스텝 크기가 변하도록 하였다. 또한 결정지향 알고리즘의 오차신호의 크기를 판단하여 어느 임계값 이상에서는 정상상태로의 빠른 수렴 속도를 유지하도록 스텝 크기가 고정인 값을 가지는 MSAG-GMMA가 동작하고, 미만일 때는 스텝 크기가 가변되는 MSAG-GMMA가 동작하도록 하였다. 제안한 알고리즘의 성능을 평가하기 위하여 성능 지수로 앙상블 ISI, 앙상블-평균 MSE, 그리고 등화기의 출력으로 얻어지는 등화 후 신호점도를 사용하였다. 모의실험을 통하여 제안한 알고리즘이 MMA, GMMA, 그리고 MSAG-GMMA보다 빠른 수렴 속도와 정상상태에서 작은 잔류 오차를 가짐을 확인하였다.

This paper is concerned with the performance analysis of a modified stop-and-go generalized multi-modulus algorithm (MSAG-GMMA) adaptive blind equalization algorithm with variable step size. The proposed algorithm multiplies the fixed step size by the error signal of the decision-oriented algorithm in the equalization coefficient update equation, and changes the step size according to the error size. Also, the MSAG-GMMA having a fixed step size is operated so as to maintain a fast convergence speed from a certain threshold to a steady state by determining the error signal size of the decision-directed algorithm, and when the MSAG-GMMA to work. To evaluate the performance of the proposed algorithm, we use the ensemble ISI, ensemble-averaged MSE, and equalized constellation obtained from the output of the equalizer as the performance index. Simulation results show that the proposed algorithm has faster convergence speeds than MMA, GMMA, and MSAG-GMMA and has a small residual error in steady state.

본 논문은 입력 전력 신호와 결정지향 오차 신호에 따라 스텝 크기가 변하는 가변 스텝 크기를 가지는 MSAGF-MMA의 성능 분석에 관한 것이다. 제안한 알고리즘은 변형된 Stop-and-Go 알고리즘으로 부터 얻어진 이진 플래그를 가지는 MMA에 스텝 크기가 입력 신호의 변동에 영향을 덜 받도록 함으로써 정상상태로의 수렴 속도를 안정하 게 높일 수 있는 입력 전력 신호에 따라 변하도록 하였다. 그와 동시에 정상상태에서 잔류 오차가 작아질 수 있도록 결정지향 오차 신호에 따라 스텝 크기가 가변될 수 있도록 하였다. 컴퓨터 모의실험 결과, 제안한 알고리즘이 MMA 및 MSAGF-MMA와 비교하여 정상상태로의 수렴 속도 면에서 뿐만 아니라 정상상태에서의 잔류 ISI와 averaged-MSE 등의 평가에서 매우 뛰어난 성능을 가짐을 확인하였다.

This paper is concerned with the performance analysis of MSAGF-MMA with variable step size whose step size varies according to input power signal and decision-directed error signal. The proposed algorithm is made to change according to the input power signal which can reliably increase the convergence speed to the steady state by making the step size less affected by the fluctuation of the input signal in the MMA having the binary flag obtained from the modified Stop-and-Go algorithm. At the same time, the step size can be varied according to the decision-directed error signal so that the residual error can be reduced in the steady state. As a result of computer simulations, it is confirmed that the proposed algorithm has a very good performance in the evaluation of residual ISI and averaged-MSE in steady state as well as in terms of convergence speed to steady state compared to MMA and MSAGF-MMA.

In this thesis, the structure of equalizer adapted to DMT system for ADSL, its performance analysis is accomplished with computer simulation, and ASIC design. There are several methods in equalization, among them by using Variable Step-Size LMS algorithm to be concerned with convergence efficiency with training sequence, and its ASIC design.

This paper presents a novel maximum power point tracking for a photovoltaic power (PV) system with a direct control plan. Maximum power point tracking (MPPT) must usually be integrated with photovoltaic (PV) power systems so that the photovoltaic arrays are able to deliver maximum available power. The maximum available power is tracked using specialized algorithms such as Perturb and Observe (P&O) and incremental Conductance (indCond) methods. The proposed method has the direct control of the MPPT algorithm to change the duty cycle of a dc-dc converter. The main difference of the proposed system to existing MPPT systems includes elimination of the proportional-integral control loop and investigation of the effect of simplifying the control circuit. The proposed method thus has not only faster dynamic performance but also high tracking accuracy. Without a conventional controller, this method can control the dc-dc converter. A simulation model and the direct control of MPPT algorithm for the PV power system are developed by Matlab/Simulink, SimPowerSystems and Matlab/Stateflow.

In this paper, we propose an optimal adaptive FIR filter, in which the step-size and error nonlinearity are simultaneously optimized to maximize the decrease of the mean square deviation (MSD) of the weight error vector at each iteration. The optimal step-size and error nonlinearity are derived, and a variable step-size stochastic information gradient (VS-SIG) algorithm is developed to approximately implement the optimal adaptation. Simulation results indicate that this new algorithm achieves faster convergence rate and lower misadjustment error in comparison with other adaptive algorithms.

In this paper, we propose a new VSS-NLMS algorithm through a simple modification of the conventional NLMS algorithm, which leads to a low complexity algorithm with enhanced performance. The step size of the proposed algorithm becomes smaller as the error signal is getting orthogonal to the input vector. We also show that the proposed algorithm is an approximated normalized version of the KZ-algorithm and requires less computation than the KZ-algorithm. We carried out a performance comparison of the proposed algorithm with the conventional NLMS and other VSS algorithms using an adaptive channel equalization model. It is shown that the proposed algorithm presents good convergence characteristics under both stationary and non-stationary environments despites its low complexity.

This paper introduces a variable step-size adaptive algorithm for blind source separation. From the frequency characteristics of mixed input signals, we need to adjust the convergence speed regularly in each frequency bin. This algorithm varies a step-size according to the magnitude of input at each frequency bin. This guarantee of the regular convergence in each frequency bin would become more efficient in separation performances than conventional fixed step-size FDICA. Computer simulation results show the improvement of about 5 dB in signal to interference ratio (SIR) and the better separation quality.

An adaptive predistorr is proposed to compensate for the nonlinear distortion of a high power amplifier (HPA) in 16 QAM system. It fumed out that the proposed predistorter using a variable step-size least mean square (VSSLMS) algorithm is stable and can reduce the Total Distortion (TD) to 0. 1dB at the HPA output backoff=0.0 dB.

The future teleconferencing systems will need an appropriate system which controls properly the acoustic echo for the convenient communication. The conventional acoustic echo cancellation algorithms involve large adaptive filters identifying the impulse response of the echo path. The use of adaptive IIR filters appears to be a reasonable way to reduce computational complexity. Effective cancellation of acoustic echo presented in teleconferencing system requires that adaptive filters have a rapid convergence speed. One of the main problems of acoustic echo cancellation techniques is that the convergence properties degrade for an highly correlated signal input such as speech signals. By the way, the introduction of linear prediction filers onto the structure of the acoustic echo cancellation represents one approach to decorrelate the speech signal. And variable step-size LMS algorithm improves the convergence speed through a little increasing of computational complexity. In this paper, we applied these two methods to the acoustic echo canceller(AEC) and showed that these methods have better performances than the conventional AEC.

본 논문에서는 적응 필터의 계수 갱신에서 가변 블록을 사용하는 방법을 제안하였다. 데이터 블록의 길이는 MSE 학습곡선의 시정수에 비례하도록 하였다. 이 방법에서는 적응 필터가 정상상태로 접근함에 따라 스텝사이즈를 조정하여 필터계수 갱신의 횟수를 줄일 수 있다. 제안한 방법의 유용성을 입증하기 위한 컴퓨터모의 실험을 통해 기존의 최적 스텝사이즈 수열을 이용한 알고리듬과 가변 스텝사이즈 알고리듬과 성능을 비교하였다. 그리고 MSE 의 초기값을 최소화하는 최적 초기 스텝사이즈를 유도하였다. 유도된 최적 스텝사이즈를 가변 스텝사이즈 알고리듬에 적용, 그 성능을 평가 하였다.

LMS 알고리즘에서, 시간영역의 적응알고리즘은 입력신호의 고유치 분포 폭이 넓게 분포되면, 수렴속도가 느려지기 때문에 가변 스텝 사이즈가 많이 사용된다. 그러나 이 경우 많은 계산량이 필요하다. 본 논문에서는 시간영역의 적응 알고리즘을 변환영역에서 수행한다. 그리고 수렴성능 향상과 계산량을 줄이기 위하여 평균오차의 순시 절대 값을 exponential 함수에 적용한 새로운 알고리즘을 제안한다. 그리고 시스템 제너레이터를 이용하여 시뮬레이션 및 검증을 하였다. 그 결과 순시 절대 값에 비례하여 변화하는 가변스텝사이즈의 적응알고리즘이 기존의 알고리즘과 비교하여 보다 안정되고 성능이 우수함을 입증하였다.

As the convergence speed of time domain adaptive algorithm on the LMS(Least Mean Square) becomes slow when eigen value distribution width is spread, So variable step size algorithm is used widely. But it needs a lot of calculation load. In this paper we consider new algorithm, which can reduce calculations and improve convergence speed, uses instantaneous absolute value of average noise signal adapting the exponential function. For the performance of proposed algorithm is tested and simulated to system generator. As the result we show the variable step size adaptive algorithm in proportion to instantaneous absolute value is more stable and efficient than others.

본 논문은 풍력발전시스템의 MPPT 제어 시 정상상태에서의 안정성 향상을 위하여 퍼지로직 기반의 듀티비 변화량 가변 MPPT 방법을 제안한다. 일정한 듀티비 변화량으로 MPPT 제어 시 추종시간이 느려지거나 최대출력 점에서 진동하는 단점이 있다. 출력 전류량에 따라 구성된 퍼지로직 기반으로 듀티비 변화량을 가변 하여 MPPT 제어 시 정상상태 특성과 시스템 응답특성을 향상 시킬 수 있다. 3kW급 계통연계형 풍력발전시스템을 기반으로 수행된 시뮬레이션 결과를 바탕으로 제안한 알고리즘의 타당성을 검증하였다.

In this paper, the simulation methods using transmission lines are studied and realized, which are necessary in design and analysis of hydraulic control systems. The basic idea of this method is that system components are separated by transmission line element for simulation. The PI-controller can keep inductance level as low as desired. It can also handle nonlinearities and discontinuities without flag signal when restarting integration. Parallel hydraulic circuits are simulated using parallel processing algorithm. To shoe that using variable timestep size in each subsystem, simulation time can be reduced. Performance of the simulation results is compared with that of Runge Kutta method.

긴 길이의 적응 필터와 높은 상관도의 입력신호를 사용하는 적응 필터링 응용에서 적응 필터의 수렴성능을 향상 시키기 위해 가변 스텝사이즈를 이용하는 부밴드 인접투사 알고리즘을 제안한다. 제안한 알고리즘은 다위상 분해와 노블아이덴티티를 적용한 M-부밴드 구조에서 각 적응 부필터별 서로 다른 스텝사이즈를 사용함으로써 빠른 수렴속도와 작은 정상상태오차를 얻을 수 있다. 각 갱신시점에서 적응 필터의 평균자승오차를 최소화하도록 유도된 스텝사이즈는 가변 스텝사이즈를 사용하는 기존 알고리즘에 비해 좋은 수렴성능을 보인다. 기존 알고리즘에 비해 우수한 제안한 알고리즘의 수렴성능을 확인하기 위해 시스템 식별 모델을 고려하여 AR(1)과 AR(2) 유색 입력 신호에 대한 최소자승편차에 대한 컴퓨터 시뮬레이션을 수행한다.

This paper presents a subband affine projection algorithm with variable step size to improve convergence performance in adaptive filtering applications with long adaptive filters and highly correlated input signals. The proposed algorithm can obtain fast convergence speed and small steady-state error by using different step sizes for each adaptive sub-filter in the subband structure to which polyphase decomposition and noble identity are applied. The step size derived to minimize the mean square error of the adaptive filter at each update time shows better convergence performance than the existing algorithm using a variable step size. In order to confirm the convergence performance of the proposed algorithm, which is superior to the existing algorithm, computer simulations are performed for mean square deviation(MSD) for AR(1) and AR(2) colored input signals considering the system identification model.