Data Communications and Information Theory Practice

Vocabulary flashcards covering the fundamentals of data communications, error detection, information theory, and source coding based on the lecture transcript.

Morse Code

A signaling system that is not considered a binary code.

Hartley Law

A law stating that the maximum rate of information transmission depends on the channel bandwidth.

Shannon-Hartley Theorem

A theorem that sets a limit on the maximum capacity of a channel with a given noise level, defined by the formula $C = B \log_{2}(1 + S/N)$.

Forward Error Correcting Codes

A scheme that corrects errors by requiring no part of the signal to be retransmitted.

Time-division Multiplex

A scheme in which several channels are interleaved and then transmitted together.

Data Communications

The transmission of voice, computer data, and video using analog or digital methods.

Serial Transmission

A transmission method preferred over parallel because it requires only a single channel.

Asynchronous Transmission

Data transmission of one character at a time using start and stop bits.

ASCII

The most widely used data communication code, which consists of $7$ bits.

Modem

A device that converts digital signals to analog and analog signals to digital.

Vertical Redundancy Check (VRC)

Another name for parity, a commonly used method of error detection.

Longitudinal Redundancy Check

An error detection method that produces a Block Check Character (BCC).

Cyclical Redundancy Check (CRC)

An error detection method where a remainder is produced by dividing the data block by a constant.

Dit

A unit of information equivalent to $3.32$ bits.

Alternate Mark Inversion (AMI)

An encoding method that uses alternating positive and negative values for 1's.

Channel Capacity

The maximum reliable information rate of a system, governed by bandwidth and the signal-to-noise ratio.

Source Coding

The process of efficiently representing data generated by a discrete source to compress data and reduce bandwidth requirements.

Entropy ($H$)

A numerical quantity that measures the uncertainty in the outcome of an experiment or the average information content of a source.

Huffman Coding

An optimal source coding technique that constructs a binary tree from the bottom up, ensuring symbols with higher probabilities receive shorter codewords.

Prefix Code

A code in which no code is the prefix of any other code, ensuring unique decodability.

Burst Error

A type of transmission error involving two or more bits.

Nats

The unit used for entropy or information content when the logarithm base $e$ (natural logarithm) is used.

Shannon-Fano Coding

A source coding technique that is generally less efficient than Huffman coding.

Coding Efficiency

A measure of how well a code represents a source, reaching $100\%$ when the entropy equals the average code length.