Papers by Keyword: Moving Average (MA)

Abstract: Chan algorithm is a closed form solution to the non-recursive equation set. This algorithm needs only a small amount of calculations but has a high degree of precision on positioning. It is valuable for academic reference. Firstly, it obtains the preliminary solution by using WLS (Weighted Least Squares) twice. Then, it uses the preliminary solution to linearise the nonlinear equation and finally makes the estimation of the position. The channel model can provide the model of indoor office environment ranging from 2 GHz to 10 GHz. Through the UWB (Ultra WideBand) positioning system of the channel model, the LOS(line-of-sight) environment can be simulated and TOA(Time-Of-Arrival) data measured by distance can also be obtained by sampling. However, small LOS errors included in the TOA data may lead to big ones in the positioning of 3D(three-dimensional) space and the precision of positioning may be undermined, when the data are directly applied to the Chan algorithm which is based on the TOA. In order to solve this issue, the TOA data obtained can be processed with MA(Moving Average) algorithm and the precision can be improved.

Abstract: Electroencephalogram (EEG) signal has conventionally been recorded with some devices, leads, an electrode cap, amplifier units, and A/D converters. The EEG signal can be contaminated by interference or sensor failures. Among the several artifact sources, an involuntary movement of patient is one of the main sources of interference in the EEG recording. The main objective of this study is to find the time of patient’s movement and to reduce noise effects from involuntary movements.

Abstract: During trajectory planning, position, velocity and acceleration should satisfy the boundary condition simultaneously, if the interpolation cycle was directly used to discrete velocity, precision loss will occur. In order to solve these problems, a novel double acceleration control algorithm in the deceleration phase is presented and used to deal with linear acc/dec control, based on which a moving-average acc/dec control algorithm is studied, this algorithm can not only meet requirement for velocity and acceleration smooth control, but also realize NC instruction interpretation with high-order differentiability. The simulation results demonstrate that the proposed algorithm is reasonable.

Abstract: Aimed at the typical problems of lower accuracy and efficiency by using traditional Kalman Filtering (KF) to model the SCATS data, a KF model based on Moving Average (KF-MA) is put forward, that is, to find out the Markov properties of the SCATS data by Moving Average model at first then model the data by Kalman Filtering. Taking the SCATS data in Hang-Zhou as an example, the KF-MA model is compared with the Time Serial (TS) model, the Time Serial model based on Moving Average (TS-MA) and the KF model. The result shows that KF-MA model can maximum elevate the computational efficiency by reducing parameters need to solved in the traditional KF models. Moreover, compared with other models, KF-MA model has better predicted accuracy.

Abstract: Recently in semiconductor industry, production of ever flatter, thinner and larger silicon wafers are required to fulfill the demands of high-density packaging and cost reduction. In geometric evaluation of Si wafers, according to SEMI (Semiconductor Equipment and Materials International) standards, the required wafer flatness approaches to the 22 nanometers by year 2016 [1]. For such application, uncertainty of measured data is encountered as a severe problem because high resolution instrument always incorporate a certain degree of noise. In order to precisely evaluate the wafer profile, it is essential to remove the noise from the measured data. Described in this paper is design and development of digital filters for denoising. Compared to the conventional low-pass filters, the developed filter by use of wavelet transform not only provides better performance of decomposition in the spatial frequency domain, but also offers the new capability of denoising in amplitude domain.