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Development of signal processing and machine learning methods for spectrum sensing using autocorrelation features

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Pubblicato in:SN Applied Sciences vol. 7, no. 11 (Nov 2025), p. 1237
Autore principale: Sesham, Srinu
Altri autori: Suresh, Nalina, Chembe, Dickson Kanungwe
Pubblicazione:
Springer Nature B.V.
Soggetti:
Wireless networks
Accuracy
Deep learning
Internet of Things
Hypothesis testing
Regression analysis
Communication
5G mobile communication
Regression models
Signal processing
Frequency ranges
Noise levels
Machine learning
Energy
Spectrum allocation
Autocorrelation
Statistical analysis
Correlation coefficients
Correlation coefficient
Learning algorithms
Fourier transforms
Sensors
Support vector machines
Methods
Eigenvalues
Performance degradation
Complexity
Signal to noise ratio
Environmental
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