comnum.theory_rs_ser#

comnum.theory_rs_ser(n, t, p_s)#

The symbol error rate after decoding, approximating that a word of i > t errors keeps its i wrong symbols (Proakis & Salehi, Sec. 7.5.2; Sklar, Digital Communications, 2nd ed., Sec. 8.1.2).

Parameters:

  • n (int) – word length (symbols).

  • t (int) – symbol errors corrected per word.

  • p_s (float | array_like) – symbol error probability of the channel.

Returns:

the decoded symbol error probability at every p_s.

Return type:

float | numpy.ndarray

Raises:

ValueError – for values that are not real numbers.

Examples

>>> import comnum
>>> bool(comnum.theory_rs_ser(255, 16, 1e-2) < comnum.theory_rs_wer(255, 16, 1e-2))
True