Information and Coding (Course No. 30)

Elements of Information, Source and Channel Coding  

Information and coding

Whenever you plan to transmit or store data, make sure you know what you're doing. Remember, there are no perfect transmission channels and no perfect storage devices. Errors happen. There is also the question of data compression: can I compress the contents of a data file down to one bit, in order to use my memory or my bandwidth more efficiently? And if that does not work, how far can I compress lossless?

Claude Shannon developed the fundamentals of the information theory in the 1940s. With its help, he was able to answer the above questions. Information in the technical sense now has a measure. Thus, we can describe the compression and transmission of date mathematically. This is the prerequisite for a successful application in practice.

In this course, participants will learn to approach typical coding problems including source and channel coding. Lots of practical examples and exercises will demonstrate how everyday engineering tasks are solved quickly and efficiently.


Profile   

Date: on demand
Duration of the course: 3 days
Location: Dübendorf (near Zürich, Switzerland)
Language: German (English on request)
Price: CHF 1950, incl. documentation and lunch


Objectives   

The course is ideal for orientation, training and consolidation. An essential component of the course are the numerous practical examples and exercises about typical industrial applications. The participant will be ready to evaluate his professional tasks, to plan strategies and to implement them. He will be familiar with the most important source and channel codes and will know about their limitations.


Contents   

Information and coding
  • Shannon's information.
  • Entropy und redundancy.
  • The source coding theorem.
  • Lossless and lossy data compression.
  • Examples: RLE, Huffman, Lempel Ziv, JPEG.
  • The channel coding theorem.
  • BSC transmission model.
  • Error detection and error correction.
  • Examples: CRC, Block Codes, Hamming, Faltungscodes.
  • Practical exercises and computer simulations.

Keywords are: information, entropy, average code length, redundancy, channel coding, entropy coding, run length encoding, Huffman code, LZ77, LZ78, LZW, JPEG, MJPEG, channel coding, foreward error correction, FEC, BSC, transmission channel, Hamming distance, block code, generator matrix, paritiy check matrix, syndrom, Hamming code, convolutional code, etc.


Prerequisites   

Basic experience in probability theory. Some mathematical skills are required. Exercises are done on your own notebook computer.


Registration   

Please contact us if you are interested. Courses take place from one participant.

Please note: If you register more than one person at the same time for the same course we grant a 15 % discount for the second person and 20 % for the third and further individuals. The number of participants is limited. Registrations are processed in chronological order. If you cancel your registration until two weeks before the course starts, we will refund your full payment. For cancellations until three working days before the course starts we refund half of your payment. We reserve the right to cancel courses. In this case, we will refund fully already payed fees.