¿Cuáles son algunas técnicas de codificación comunes para reducir la redundancia y el ruido de los datos?

RLE is a coding technique that provides efficiency by reducing data redundancy and noise in coding. Your data is filled with symbols and characters, so RLE works by replacing repeated characters or symbols with a count value and the character itself. It cleverly compresses long strings of the same character by tallying them up. This method drastically reduces the amount of storage required. You can use RLE in image compression and data transmission, offering a huge space savings without losing any information. In short, Run-length encoding conquers data clutter!

Normalization: Organizing data to minimize redundancy by ensuring that data attributes are stored in only one place. Data Compression: Using algorithms to reduce the size of data, thereby minimizing redundancy and noise. Error Detection and Correction: Implementing techniques such as checksums and error-correcting codes to detect and correct errors in data, reducing noise. Data Deduplication: Identifying and eliminating duplicate data within a dataset, reducing redundancy.

Run-length encoding (RLE) compresses data by replacing repeated sequences with a single value and count. For example, "AAAAABBBBCCCC" becomes "5A4B4C". It's effective for compressing data with long runs of the same value, like images, text, or audio, reducing size and eliminating redundancy.

Huffman coding assigns variable-length codes to data based on frequency, with frequent data getting shorter codes. For example, "ABRACADABRA" becomes "01101110100010101101110" (A=0, B=10, R=110, C=1110, D=1111). It's effective for compressing data with skewed value distributions, like text, audio, or video, reducing size and minimizing noise.

Error correction coding (ECC) adds extra bits to data to detect and correct errors during transmission or storage. For example, "10011010" becomes "10011010111" using a parity check code, enabling error verification and correction. While ECC increases data size, it enhances reliability, useful for noisy environments like wireless or optical signals.

Data encryption transforms data into a secret format accessible only by authorized parties. For instance, "HELLO" encrypted as "URYYB" using a Caesar cipher shifts each letter by 13 positions. Encryption safeguards data from unauthorized access, modification, or disclosure without affecting data size, enhancing security and confidentiality for sensitive information like passwords or messages.