Statistics and Machine Learning for Behavioral Prediction of Operational Transconductance Amplifiers with Focus on Regression Analysis

Ivanova, Malinka; Petkova, Petya; Petkov, Nikolay

doi:10.1007/978-981-16-8885-0_25

Cited by 2 publications

(1 citation statement)

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“…In polynomial regression, the use of polynomial changes is a low-dimensional and high-dimensional method for linear models [10]. Usually, as long as the degree of an independent variable is set (greater than 1), the result of data mapping in a high-dimensional space can be obtained.…”

Section: Polynomial Regressionmentioning

confidence: 99%

Research on communication signal waveform technology of aerospace telemetry track and command network based on polynomial regression

Hu,

Zhang

2023

Second International Conference on Applied Statistics, Computational Mathematics, and Software Engineering (ASCMSE 2023)

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In recent years, due to the development of communication measurement and control technology and the rise of artificial intelligence technology, the construction of intelligence and informatization has become the main direction of China's wireless communication application field in the future. However, due to the increasingly scarce spectrum resources, the interference in the communication environment is complex and changeable. With the development of technology, artificial intelligence uses a large number of structured data mining methods to fit nonlinear information systems. This paper considers the relationship between communication signal waveform parameters and environmental SNR and bit error rate in aerospace measurement and control scenarios, and proposes to use polynomial regression algorithm to build an adaptive parameter learning model, while using the grid search hyperparameter optimization method to find the optimal combination of hyperparameters.

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Section: Polynomial Regressionmentioning

confidence: 99%