Weak signal detection under the condition of adiabatic elimination in large parameters has been solved by step-changed stochastic resonance algorithm. Adaptive stochastic resonance based on approximate entropy measurement is proposed, and it can give the best result of the step-changed stochastic resonance adaptively. Because the approximate entropy of the periodic signal does not suffer from the change of its amplitude and phase, a periodic signal of frequency f0 with given signal-to-noise ratio which is to be detected can be made under the same condition as the raw data, and its approximate entropy is calculated as the criterion. By adjusting the structural parameters and calculation step automatically, a series output of the bistable system can be got, and an approximate entropy distance matrix can be constructed. After getting the minimum value of the matrix, the best parameters of the nonlinear dynamical system can be obtained.