Communications Blockset

Source Coding

Source coding, also known as quantization or signal formatting, is a way of processing data in order to reduce redundancy or prepare it for later processing. Analog-to-digital conversion and data compression are two categories of source coding.

Source coding divides into two basic procedures: source encoding and source decoding. Source encoding converts a source signal into a digital signal using a quantization method. The symbols in the resulting signal are nonnegative integers in some finite range. Source decoding recovers the original information from the source coded signal.

For background material on the subject of source coding, see the works listed in Selected Bibliography for Source Coding.

Source Coding Features of the Blockset

This blockset supports scalar quantization, predictive quantization, companders, and differential coding. It does not support vector quantization. You can open the Source Coding library by double-clicking its icon in the main Communications Blockset library (commlib), or by typing

• commsrccod2
  

at the MATLAB prompt.

Blocks in the Source Coding library can

• Use a partition and codebook to quantize a signal
• Implement differential pulse code modulation (DPCM)
• Compand a signal using a µ-law or A-law compressor or expander
• Encode or decode a signal using differential coding

Supporting functions in the Communications Toolbox also allow you to optimize source coding parameters for a set of training data. See the sections Optimizing Quantization Parameters and Optimizing DPCM Parameters in the Communications Toolbox User's Guide for more information about such capabilities.

Example: Viewing a Sinusoid

Representing Quantization Parameters