10_Information Theory Flashcards
What is the purpose of redundancy in data?
Redundancy in data helps detect and correct errors by reducing entropy and increasing predictability.
What is channel capacity in information theory?
Channel capacity is the maximum rate of data transmission over a channel without errors, measured in bits per second.
What does the Noiseless Coding Theorem describe?
It describes the limit to which data can be compressed without losing any information, defining the minimum size of encoded data.
How does the Shannon-Hartley theorem apply to communications?
It connects a communication channel’s capacity to its bandwidth and signal-to-noise ratio, calculating the maximum data rate for noisy channels.
What is mutual information?
Mutual information measures how much knowing one variable reduces uncertainty about another, quantifying information shared between variables.
Define source coding.
Source coding is compressing information into fewer bits than the original representation to make data storage and transmission more efficient.
How does information theory impact network theory?
It optimizes data flow and routing in networks by applying principles of efficient data transmission and error handling.
What are error-correcting codes and their significance?
Error-correcting codes add redundancy for detecting and correcting transmission errors, crucial for keeping data integrity.
What is rate-distortion theory?
Rate-distortion theory studies the trade-off between the rate of data transmission and the quality distortion, important for understanding limits of compression.
How is information theory applied in cryptography?
Information theory helps design secure cryptographic systems by ensuring keys and ciphers are unpredictable and robust against decoding.