PPT-Codes with local decoding procedures

Sergey Yekhanin Microsoft Research Errorcorrecting codes paradigm 0110001 011000100101 0110001 01 00 10010 Encoder Decoder Channel   noise       The paradigm dates back to 1940s Shannon Hamming. 6. . Channel . Coding. Motivation. Wireless channel introduces errors due to. Noise and Interference. Multipath Effect resulting in fast fading. Option A. Increase power of transmission. Waste of energy and interference. under Packet Erasures. Derek Leong. *#. , . Asma. . Qureshi. *. , and Tracey Ho. *. *. California Institute of Technology, Pasadena, California, USA. #. Institute for . Infocomm. Research, Singapore. Sergey Yekhanin. Microsoft Research. Data storage. Store data reliably. Keep it readily available for users. Data storage: Replication. Store data reliably. Keep it readily available for users. Very large overhead. 11K-3 Decoding SkillsPhonics/Sequential Decoding T he role of phonics in beginning reading instruction has been the topicof what seems like endless discussion and debate; the consensusamong the docume Bin Li. ， . Senior. . Technical. . Expert. Huawei. Technologies. NASIT, San Diego, August 13. th. , 2015. Contents. Polar Codes for 5G. Performance Comparisons. Low-Complexity Parallel SC-List Decoder. Partial Information Rewriting for Flash Memories. Yue Li. joint work with . Anxiao. (Andrew) Jiang and . Jehoshua. . Bruck. Block Erasure is Harmful. Decreasing cell level triggers block erasure. E. Separability. Matrix for ECOC coding. Miguel Angel Bautista, Sergio . Escalera. , Xavier . Baró. & . Oriol. . Pujol. 1. Outline. Classification problems and the ECOC . framework.. Motivation. 6. . Channel . Coding. Motivation. Wireless channel introduces errors due to. Noise and Interference. Multipath Effect resulting in fast fading. Option A. Increase power of transmission. Waste of energy and interference. Andrew . Hagedorn. , . Sachin Agarwal , David Starobinski, and Ari Trachtenberg. Department . of ECE, Boston . University, MA, USA. IEEE INFOCOM 2009. 1. Outline. Introduction. Problem . Definition. Shifted LT (SLT) Codes. Huffman Codes. Unique Decodability. We must always be able to determine where one code word ends and the next one begins. Counterexample: . Suppose: . s. 1. = 0; . s. 2. = . 1; . s. 3. = 11; . s. Convolutional Codes COS 463 : Wireless Networks Lecture 9 Kyle Jamieson [Parts adapted from H. Balakrishnan ] So far, we’ve seen block codes Convolutional Codes: Simple design, especially at the transmitter Convolutional Codes COS 463 : Wireless Networks Lecture 9 Kyle Jamieson [Parts adapted from H. Balakrishnan ] So far, we’ve seen block codes Convolutional Codes: Simple design, especially at the transmitter Paulo S. L. M. Barreto. University of Washington | Tacoma. Objectives. Basics of coding theory.. Security considerations.. Panorama of code-based cryptosystems.. Choice of codes.. Implementation issues.. Paul Cuff. Curt . Schieler. Source-Channel Coding. p(. y|x. ). f. g. Correlation between S and Ŝ:. Achieved with separately designed encoder and decoder.. Video Transmission (example). p(. y|x. ). f.