Bayesian step least mean squares algorithm for Gaussian signals

Lopes, Paulo A. C.

doi:10.1049/iet-spr.2020.0058

Cited by 5 publications

(1 citation statement)

References 28 publications

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“…Bayesian estimation of PDF from data and assumption of Gaussian reference and measurement noise signals were also used. The experimental results showed the effectiveness of the method to select the optimal step size of the LMS algorithm [14]. Liu et al designed a personalized book recommendation system for child-robot interaction environments in order to help children read books more conveniently.…”

Section: Related Workmentioning

confidence: 99%

Recruiting PE Teachers Based on Regional Socio-Economic Status Evaluation and Recommendation Algorithm

Long,

2023

JAIT

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The most important step in creating a teaching force for physical education (PE) is finding enough qualified teachers. In order to better absorb the PE teaching talents who are more suitable for the job requirements, the ability variables of sports talents, the expected regional social and economic status, and historical data are considered, the intelligent matching of talents and positions is made, and the Bayesian variational network recommendation model considering the needs are constructed. According to the experimental findings, this model's highest recommendation accuracy in the normal scenario is 0.5888 and its maximum recommendation accuracy in the training and test sets is roughly 0.6 and 0.68. The model has good convergence and high accuracy of recommendation, which is conducive to matching PE teaching talents and teaching positions, providing job seekers with positions that meet their needs, providing teaching talents to meet the requirements, and creating a team of PE teachers that match people and posts.

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Section: Related Workmentioning

confidence: 99%

Recruiting PE Teachers Based on Regional Socio-Economic Status Evaluation and Recommendation Algorithm

Long,

2023

JAIT

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Research on pipeline leakage localization method based on CZIM algorithm

Yue,

Qu,

Yan

et al. 2024

Appl Water Sci

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The time difference of arrival is a common method to find the leakage point of water pipeline. The leakage point localization is achieved by calculating the time delay between the signals reaching different sensors. Mainstream time delay estimation algorithms based on signal correlation analysis are susceptible to the introduction of noise signals, low sampling rates, and signal clipping, resulting in inaccurate localization results. The article analyzed the impact of different interference factors and proposed a new time delay estimation algorithm based on signal cross-zero information modulation (CZIM) to address these problems. By normalizing the amplitude of the two signals at the detection points on both sides of the pipeline leakage position, two sets of sparse signal sequences with only two eigenvalues of 0 and 1 are obtained. The error coefficient function is calculated by a similar traversal method to finally index the time delay. In this paper, the principle and characteristics of the algorithm are analyzed and compared with the most commonly used GCC method. In both numerical simulations and actual pipe leakage localization experiments, the CZIM algorithm has shown its wide applicability, low impact by low sampling rate, and adaptability to low signal-to-noise ratios, etc. At the same time, the algorithm is simple in design and has a small amount of calculation and can meet the demand for real-time data processing, providing a new idea for the development of acoustic localization technology.

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