Every non-systematic linear code can be transformed into a systematic code with essentially the same properties (i.e., minimum distance).23 Because of the advantages cited above, linear error-correcting codes are therefore generally implemented as systematic codes. However, for certain decoding algorithms such as sequential decoding or maximum-likelihood decoding, a non-systematic structure can increase performance in terms of undetected decoding error probability when the minimum free distance of the code is larger.45
For a systematic linear code, the generator matrix, G {\displaystyle G} , can always be written as G = [ I k | P ] {\displaystyle G=[I_{k}|P]} , where I k {\displaystyle I_{k}} is the identity matrix of size k {\displaystyle k} .
James L. Massey, Daniel J. Costello, Jr. (1971). "Nonsystematic convolutional codes for sequential decoding in space applications". IEEE Transactions on Communication Technology. 19 (5): 806–813. doi:10.1109/TCOM.1971.1090720. S2CID 51650729.{{cite journal}}: CS1 maint: multiple names: authors list (link) /wiki/James_L._Massey ↩
Richard E. Blahut (2003). Algebraic codes for data transmission (2nd ed.). Cambridge. Univ. Press. pp. 53–54. ISBN 978-0-521-55374-2. 978-0-521-55374-2 ↩
Shu Lin; Daniel J. Costello, Jr. (1983). Error Control Coding: Fundamentals and Applications. Prentice Hall. pp. 278–280. ISBN 0-13-283796-X. 0-13-283796-X ↩