is the mathematical study of the quantification, storage, and communication of information. It was founded by Claude Shannon in his landmark 1948 paper, "A Mathematical Theory of Communication" , which introduced a probabilistic framework to address the fundamental limits of communication.
Hamming codes, Reed-Solomon codes (used in CDs), and modern Low-Density Parity-Check (LDPC) or Polar codes (used in 5G). 4. Summary of Key Differences Source Coding Channel Coding Primary Goal Efficiency (Compression) Reliability (Error Correction) Action Removes redundancy Adds redundancy Metric Channel Capacity ( Timing Performed before transmission Performed during/for transmission 5. Modern Applications Information and Coding Theory
Modern image and video compression often integrate classical rate-distortion theory with neural networks. is the mathematical study of the quantification, storage,
): The maximum rate at which information can be reliably transmitted over a noisy channel. ): The maximum rate at which information can
Shannon proved that if the transmission rate ( ) is less than the capacity ( ), error-free communication is possible. 3. Branches of Coding Theory