(3) Resample {x i t |i = 1, . . . , m} with probability proportional to w(x i t ) to renew the m samples as following an empirical distribution πt (x t ) = 1 m m i=1 I(x t = x i t ) with the equal weight as in Eq. 17. In step 1, the previous sample set is tentatively replaced with a new one according to the proposal distribution η(x t |x i t-1 ). The proposal distribution is designed to search a neighboring area of the currently obtained x i t-1 with a certain probability and to search a still unexplored region with the remaining probability. This strikes a balance between exploitation and exploration. In step 2, we calculate the importance weight representing the goodness-of-fit of the proposed x i t . Finally, in step 3, we determine the survival or death of x i t according to the importance weight. The SMC is essentially equivalent to a genetic algorithm.