List questions from information-theory

Published on 28 Dec 2014 - 20:53

440

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Is Entropy = Information circular or trivial?

Published on 28 Mar 2026 - 1:12

128

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Absolute value of difference between entropies (of two distributions)

Published on 26 Mar 2026 - 22:14

170

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Proving or disproving concavity of a function

Published on 01 Jan 2015 - 9:22

161

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Why does a rate close to $1$ make a code less 'useful'?

Published on 27 Mar 2026 - 22:01

208

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Intuition behind defining the information of a random variable as being additive for independent events

Published on 23 Feb 2026 - 1:06

220

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Entropy analysis in Laplacian pyramid

Published on 25 Mar 2026 - 20:38

78

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Entropy: Proving "information gain" formula: $h(x) = -\log p(x)$

Published on 04 Oct 2019 - 5:10

60

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Suppose that E and F are systems of events in a finite probability space...

Published on 05 Oct 2019 - 21:13

229

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Integral change of random variables with linear vector equation: y=Ax

Published on 06 Oct 2019 - 2:50

4k

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Conditional Entropy: if $H[y|x]=0$, then there exists a function $g$ such that $y=g(x)$

Published on 27 Mar 2026 - 0:03

47

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Relationship between code length and predicted distribution

Published on 27 Mar 2026 - 21:53

64

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Capacity of Markov Channel

Published on 28 Mar 2026 - 11:19

590

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How do I prove that additive joint entropy implies random variables are independent?

Published on 13 Oct 2019 - 8:55

233

Views

Assuming uniform distribution of input messages

Published on 27 Mar 2026 - 21:56

List Question

Is Information Theory Mathematics?

Is Entropy = Information circular or trivial?

Absolute value of difference between entropies (of two distributions)

Proving or disproving concavity of a function

Why does a rate close to $1$ make a code less 'useful'?

Intuition behind defining the information of a random variable as being additive for independent events

Entropy analysis in Laplacian pyramid

Entropy: Proving "information gain" formula: $h(x) = -\log p(x)$

Suppose that E and F are systems of events in a finite probability space...

Integral change of random variables with linear vector equation: y=Ax

Conditional Entropy: if $H[y|x]=0$, then there exists a function $g$ such that $y=g(x)$

Relationship between code length and predicted distribution

Capacity of Markov Channel

How do I prove that additive joint entropy implies random variables are independent?

Assuming uniform distribution of input messages

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