Entropy (information theory)

Applied sciences
Information engineering
Information theory
Channel capacity

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Related lectures (30)

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Quantifying Entropy in Neuroscience Data

Delves into quantifying entropy in neuroscience data, exploring how neuron activity represents sensory information and the implications of binary digit sequences.

Conditional Entropy and Information Theory Concepts

Discusses conditional entropy and its role in information theory and data compression.

Random Walks and Moran Model in Population Genetics

Explores random walks, Moran model, bacterial chemotaxis, entropy, information theory, and coevolving sites in proteins.

Entropy and the Second Law of Thermodynamics

Covers entropy, its definition, and its implications in thermodynamics.

Entropy Bounds: Conditional Entropy Theorems

Explores entropy bounds, conditional entropy theorems, and the chain rule for entropies, illustrating their application through examples.

Information Theory Basics

Introduces information theory basics, including entropy, independence, and binary entropy function.

Chapter 3: Entropy of Subsystems

Covers entropy in subsystems, reversible processes, equilibrium, and simple systems.

Quantifying Randomness and Information in Biological Data

Explores entropy, randomness, and information quantification in biological data analysis, including neuroscience and protein structure prediction.

Information Theory: Quantifying Messages and Source Entropy

Covers quantifying information in messages, source entropy, common information, and communication channel capacity.

Heat Transfer: Equilibrium Approach and Thermodynamic Potentials

Reviews heat transfer mechanisms, entropy, and thermodynamic potentials in relation to equilibrium and Carnot cycles.