[[Code]]

Overview of various encoding techniques, focusing on transforming information into symbolic representations like Morse code, fixed-length, and variable-length codes. It also discusses the principles of encoding systems used in technology and communication.

[[Shanon-Fano method | Shannon-Fano method]]

The Shannon-Fano method is a basic data compression technique where symbols are arranged by their probability of occurrence. The goal is to assign shorter codes to more frequent symbols, optimizing data encoding efficiency

[[Encoding integers]]

Explains various methods for encoding integers, focusing on binary representation and how to handle both positive and negative numbers using sign-magnitude and two's complement methods. It includes practical examples, such as converting between decimal and binary systems and performing arithmetic with binary numbers.

[[BCD encoding]]

Representing each decimal digit (0-9) with a 4-bit binary sequence, BCD simplifies conversion between binary and decimal

[[Fixed-Point Number Representation]]

A method for encoding real numbers where the decimal point's position is fixed, offering hardware simplicity and uniform precision.

[[Floating-Point representation]]

Explains how real numbers are stored using the IEEE 754 standard. The number is divided into sign, exponent, and mantissa for efficient handling of large or small values.

[[Parity Check]]

A simple error detection method used in data transmission and storage, ensuring data integrity by verifying the even or odd number of 1 bits in binary sequences.

[[Error detection and correction]]

Techniques like Elias-style block protection and Hamming codes are explained, focusing on detecting and correcting single-bit errors to maintain data integrity during transmission

[[Luhn algortithm to protect Credit card numbers]]

We can use the Luhn algorithm to check if a credit card number is valid.