Covers information measures like entropy, Kullback-Leibler divergence, and data processing inequality, along with probability kernels and mutual information.
Covers information measures like entropy, joint entropy, and mutual information in information theory and data processing.
Discusses mutual information, data processing inequality, and properties related to leakage in discrete systems.
Covers information measures, tail bounds, subgaussions, subpossion, independence proof, and conditional expectation.
Covers variational representation and information measures such as entropy and mutual information.
Covers the basics of information theory, focusing on Shannon's setting and channel transmission.
Explores mutual information for quantifying statistical dependence between variables and inferring probability distributions from data.
Explores achievable rate, channel capacity, spectral efficiency, and fading channels in wireless communication systems.
