⋆ Figure 1 shows the output (y_{k}) of equation (21) of the 10th iteration and the reference trajectory (y_{d}).
The model was fit within the Bayesian framework using JAGS v2.2.0, with four independent chains each run for 100 000 iterations following a burn-in period of 1 000 iterations, and every 10th iteration retained for subsequent analysis (see Additional file 1: Appendix for mathematical formulation).
While the message-passing decoding of a rate-0.75 PA code at the 10th iteration requires about operations per data bit [4], the log-domain BCJR decoding of a rate-0.75 turbo code at the 6th iteration requires as many as operations per data bit, a complexity times larger.
After a burn in period of 40,000 iterations, parameter estimates were obtained from a further 80,000 iterations (with every 10th iteration kept).
Figure 4 Max tracking error on the iteration domain for Case 2. Figure 5 System output profiles for Case 2: (a) 1st iteration; (b) 10th iteration; (c) 50th iteration.
To see the convergence procedure more clearly, system outputs at 1st, 10th and 50th iteration are plotted in Figure 3. Figure 2 Max tracking error on the iteration domain for Case 1. Figure 3 System output profiles for Case 1: (a) 1st iteration; (b) 10th iteration; (c) 50th iteration.
