Analysis on the adaptive filter based on LMS algorithm

Zhu, Zhen; Gao, Xiang; Cao, Leilei; Pan, Daoyuan; Cai, Yumeng; Zhu, Yu

doi:10.1016/j.ijleo.2016.02.005

Cited by 27 publications

(19 citation statements)

References 29 publications

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“…The simulation results of the proposed Taylor‐BLMS model is compared with the other existing beamforming algorithms, namely, Wiener beamforming, LMS beamforming, BLMS beamforming, and FOBLMS algorithms. The comparative models utilized in this research is briefed as follows.…”

Section: Resultsmentioning

confidence: 99%

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Multipath mitigation in GPS receiver using Taylor integrated bidirectional least mean square algorithm

Siridhara

Ratnam

2019

Trans Emerging Tel Tech

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Research interest in Global Navigation Satellite System (GNSS) is increasing in the past few years due to its wide applicability in many application-oriented environments, such as automobile navigation system and aircraft landing system. Global Positioning System (GPS) is one of the GNSSs having high precision navigation performance. Multipath is a dominant error source that occurs in several GPS applications, limiting the performance. To reduce the multipath effects of satellite signals, an effective multipath mitigation technique is required. This paper introduces the Taylor series-based bidirectional least mean square (Taylor-BLMS) beamforming model for the multipath mitigation problems occurring in the GPS receiver. The performance metrics, such as antenna gain and bit error rate (BER), measure the performance of the proposed Taylor-BLMS model against various comparative models. For the system with six sensors, the proposed Taylor-BLMS model has the best performance with the values of 23.460 dB and 4.78E−05 for the antenna gain and the BER, respectively. For the system with 1 jammer, the proposed Taylor-BLMS model has the antenna gain and the BER values of 22.2828 dB and 3.69E−05, respectively. Trans Emerging Tel Tech. 2019;30:e3760. wileyonlinelibrary.com/journal/ett

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Section: Resultsmentioning

confidence: 99%

“…LMS beamforming : The LMS model reduces the error value by adjusting the weights in the forward direction only.…”

Section: Resultsmentioning

confidence: 99%

Multipath mitigation in GPS receiver using Taylor integrated bidirectional least mean square algorithm

Siridhara

Ratnam

2019

Trans Emerging Tel Tech

View full text Add to dashboard Cite

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“…The LMS filter updates its filter coefficients according to least mean squares algorithm; computation proceeds according to Equations (17)- (19) [36]:…”

Section: Lms Filtermentioning

confidence: 99%

“…To the best of our knowledge, adaptive filters have rarely been applied in solar radiation estimation. Among digital filters used in applications, the adaptive filter [34,35] is advantageous compared with the finite impulse response (FIR) filter and infinite impulse response (IIR) filter due to its better performance in situations with a spectrum overlap between the signal and noise [36]. Adaptive filters are widely used in many fields such as noise canceling, system identification, and signal prediction [37,38].…”

Section: Introductionmentioning

confidence: 99%

Estimation of Solar Radiation for Tomato Water Requirement Calculation in Chinese-Style Solar Greenhouses Based on Least Mean Squares Filter

Zhang

et al. 2019

Sensors

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The area covered by Chinese-style solar greenhouses (CSGs) has been increasing rapidly. However, only a few pyranometers, which are fundamental for solar radiation sensing, have been installed inside CSGs. The lack of solar radiation sensing will bring negative effects in greenhouse cultivation such as over irrigation or under irrigation, and unnecessary power consumption. We aim to provide accurate and low-cost solar radiation estimation methods that are urgently needed. In this paper, a method of estimation of solar radiation inside CSGs based on a least mean squares (LMS) filter is proposed. The water required for tomato growth was also calculated based on the estimated solar radiation. Then, we compared the accuracy of this method to methods based on knowledge of astronomy and geometry for both solar radiation estimation and tomato water requirement. The results showed that the fitting function of estimation data based on the LMS filter and data collected from sensors inside the greenhouse was y = 0.7634x + 50.58, with the evaluation parameters of R2 = 0.8384, rRMSE = 23.1%, RMSE = 37.6 Wm−2, and MAE = 25.4 Wm−2. The fitting function of the water requirement calculated according to the proposed method and data collected from sensors inside the greenhouse was y = 0.8550x + 99.10 with the evaluation parameters of R2 = 0.9123, rRMSE = 8.8%, RMSE = 40.4 mL plant−1, and MAE = 31.5 mL plant−1. The results also indicate that this method is more effective. Additionally, its accuracy decreases as cloud cover increases. The performance is due to the LMS filter’s low pass characteristic that smooth the fluctuations. Furthermore, the LMS filter can be easily implemented on low cost processors. Therefore, the adoption of the proposed method is useful to improve the solar radiation sensing in CSGs with more accuracy and less expense.

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“…Zhu et al [6] proposed a PSS based on requirement analysis and knowledge management for aircraftmaintenance.…”

mentioning

confidence: 99%

A knowledge based machine tool maintenance planning system using case-based reasoning techniques

Wan

Gao

et al. 2019

Robotics and Computer-Integrated Manufacturing

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In advanced manufacturing systems,Computer Numerical Control (CNC) machine tools are importantequipment to manufacture product components of high precision, whilst from equipment maintenance point of view, they areregarded as the 'products' provided by machine tool manufacturers. Therefore, the reliability of CNC machine tools affects not only the quality of the componentsthey manufacture, but also the reputation and profits of equipment suppliers. This paper presents a novel knowledge based maintenance planning system to facilitate information and knowledge sharing between all stakeholders including machine tool manufacturers, users (manufacturing systems), maintenanceservice providers and part suppliers (for machine tools), in the emerging 'Product-Service' business model.Case Based Reasoning principles have been implementedto improve the efficiency of maintenance planning. Ontologieswere adopted to represent field knowledge using adaptation guided retrievalsbased on semantic similarity and correlation. The adaption algorithm has been developed based on the Casual Theory and the dependence relationship to generate the solution forrequiredmaintenance problems. The proposedsystem was implemented using Content Management technologies, which proved to have advantages over traditional database systems in managing engineering knowledge, andhas been verified using an example CNC machine tool. The results were commented by industrial collaborators as very promising and further exploitation in industry was recommended.

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Analysis on the adaptive filter based on LMS algorithm

Cited by 27 publications

References 29 publications

Multipath mitigation in GPS receiver using Taylor integrated bidirectional least mean square algorithm

Multipath mitigation in GPS receiver using Taylor integrated bidirectional least mean square algorithm

Estimation of Solar Radiation for Tomato Water Requirement Calculation in Chinese-Style Solar Greenhouses Based on Least Mean Squares Filter

A knowledge based machine tool maintenance planning system using case-based reasoning techniques

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