Channel capacity (baud rate) @ArtOfTheProblem

Art of the Problem | Channel capacity (baud rate) @ArtOfTheProblem | Uploaded 11 years ago | Updated 11 hours ago
Introduction to channel capacity, symbol rate (baud) & message space. This is the first step towards more modern measures of information. Featuring the Baudot multiplex system & Thomas Edison's quadruplex telegraph.

Play with the pulse generator!
http://www.khanacademy.org/cs/symbol-rate-exploration/1528686552
Play with message space generator!
http://www.khanacademy.org/cs/message-space-exploration-edit-copy/1528863275
References:
Transmission of Information - R. V. L. Hartley

An Introduction to Information Theory: Symbols, Signals and Noise - John R. Pierce

Intro to Channel Capacity (Information Theory)

$Gambling with Secrets: Part 6/8 (Perfect Secrecy & Pseudorandomness) This chapter introduces why random shifts result in perfect secrecy. We explore hardware random number generators vs. pseudorandom number generators which expand a short random seed into a long sequences of random looking numbers. If used in cryptography, can offer practical security which is based on the secrecy of the random seed only. Alice and Bob can safely assume that the enemy knows the system (one-time pad + pseudorandom generator), and focus on assuring their seed is shared in secret & generated randomly. If you are still wondering: how exactly would Eve break a ciphertext encrypted with a pseudorandom list of shifts? Remember: the pseudorandom generator can only produce a tiny (0.0000...1%) fraction of all possible shift sequences. Eve could program a computer to generate all possible sequences (starting from seed 0, 1, 2, 3.....) and reverse all of these shifts. When the computer hits a seed which decrypts the ciphertext into an English looking sentence, she can be 99.999% sure it is the message. All of the other seeds will decrypt into unreadable (jumbled looking) messages.$

Teaser Trailer: Gambling with Secrets (pilot episode)

Is Intelligence related to prediction? #ai #chatgpt #technology #ailearning

Randomized Algorithms (Prime Adventure part 8)

Why are random numbers hard to generate? (Frequency Stability)

How AI Systems Represent Concepts #ai #ailearning