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  2. Shannon–Hartley theorem - Wikipedia

    en.wikipedia.org/wiki/Shannon–Hartley_theorem

    It connects Hartley's result with Shannon's channel capacity theorem in a form that is equivalent to specifying the M in Hartley's line rate formula in terms of a signal-to-noise ratio, but achieving reliability through error-correction coding rather than through reliably distinguishable pulse levels.

  3. Channel capacity - Wikipedia

    en.wikipedia.org/wiki/Channel_capacity

    Channel capacity, in electrical engineering, computer science, and information theory, is the theoretical maximum rate at which information can be reliably transmitted over a communication channel.

  4. Noisy-channel coding theorem - Wikipedia

    en.wikipedia.org/wiki/Noisy-channel_coding_theorem

    In information theory, the noisy-channel coding theorem (sometimes Shannon's theorem or Shannon's limit), establishes that for any given degree of noise contamination of a communication channel, it is possible (in theory) to communicate discrete data (digital information) nearly error-free up to a computable maximum rate through the channel.

  5. Data signaling rate - Wikipedia

    en.wikipedia.org/wiki/Data_signaling_rate

    The maximum user signaling rate, synonymous to gross bit rate or data signaling rate, is the maximum rate, in bits per second, at which binary information can be transferred in a given direction between users over the communications system facilities dedicated to a particular information transfer transaction, under conditions of continuous transmission and no overhead information.

  6. Data compression ratio - Wikipedia

    en.wikipedia.org/wiki/Data_compression_ratio

    For example, uncompressed songs in CD format have a data rate of 16 bits/channel x 2 channels x 44.1 kHz ≅ 1.4 Mbit/s, whereas AAC files on an iPod are typically compressed to 128 kbit/s, yielding a compression ratio of 10.9, for a data-rate saving of 0.91, or 91%.

  7. Entropy (information theory) - Wikipedia

    en.wikipedia.org/wiki/Entropy_(information_theory)

    The entropy rate of a data source is the average number of bits per symbol needed to encode it. Shannon's experiments with human predictors show an information rate between 0.6 and 1.3 bits per character in English; [21] the PPM compression algorithm can achieve a compression ratio of 1.5 bits per character in English text.

  8. Backpacks full of $1.1 million worth of cocaine found near ...

    www.aol.com/news/backpacks-full-1-1-million...

    Agents on patrol discovered two backpacks stuffed with more than $1.1 million worth of cocaine in Washington state near the border with Canada, U.S. Customs and Border Protection said Monday.

  9. Symbol rate - Wikipedia

    en.wikipedia.org/wiki/Symbol_rate

    The difference between baud (or signaling rate) and the data rate (or bit rate) is like a man using a single semaphore flag who can move his arm to a new position once each second, so his signaling rate (baud) is one symbol per second. The flag can be held in one of eight distinct positions: Straight up, 45° left, 90° left, 135° left ...