Browsing by Author "Liu, GS"

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Analysis of adaptive LMS estimator with cyclic sequences in complex frequency domain
(1995-12-01)
Liu, GS
;
Wei, CH
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電控工程研究所
;
電信研究中心
;
Institute of Electrical and Control Engineering
Cyclic sequences are usually employed as the reference sequences in the adaptive filtering systems for signal or channel estimation, In this situation, the stability of an adaptive filter can be analyzed by an equivalent transfer function in complex frequency domain, For several special classes of cyclic reference sequences, the stability bounds of the adaptive filter with least mean-square (LMS) algorithm and its variants, leaky-LMS (L-LMS) and minimum output variance LMS (MOV-LMS), are obtained. Effects of these algorithms on the resultant transfer functions and the stability bounds are also investigated.
Grey prediction model for forfcasting the planning material of equipment spare parts in navy of Taiwan
(2004)
Chiou, HK
;
Tzeng, GH
;
Cheng, CK
;
Liu, GS
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科技管理研究所
The inventory management of maintenance spare pails plays all important role on their logistic policy. However, for the reasons of insufficient data or uncertain demand of maintenance requirement that we have, the traditional forecasting method is generally hard to predict the optimal quantity of spare parts fitting the requirement. In this Study, we introduce Grey Prediction Model (GPM) to coping with such problem. After taking three types weapon system periodic items of planning material from 1999 to 2002, we then apply GM(1,1) model to predict the planning requirement of intermittent spare parts of 2003. In order to verify the performance of our forecasting model, we also compare the results With the observed data which are calculated by the rule of technical manual of equipments. Through this Study, we demonstrate that the GM(1,1) conduct a good accuracy on prediction of spare pails especially in Sialations of insufficient data, which accurate prediction should reduce the operation cost and improve the reliability of maintenance equipment.
Quadrilevel periodic sequences for fast start-up equalization and channel estimation
(1996-02-01)
Liu, GS
;
Wei, CH
;
電控工程研究所
;
Institute of Electrical and Control Engineering
A class of four-level periodic sequences derived from the binary m-sequences are presented. These sequences can be used as the training sequences in adaptive channel estimation and equalization with fast start-up for multilevel PAM or QAM transmission. The sequence generator can be implemented by simple hardware.