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Explores the quality of Integrate-and-Fire models in computational neuroscience through comparisons with experimental data and mathematical predictions.
Explores mapping non-linear data to higher dimensions using SVM and covers polynomial feature expansion, regularization, noise implications, and curve-fitting methods.
Explores noise and propagation fundamentals in radiation, antennas, and wireless communications, covering internal and external noise sources, thermal noise, wireless principles, and signal propagation phenomena.
