An adaptive algorithm for extracting weak signal based on the theory of stochastic resonance(SR) was proposed. It was implemented by investigating the self correlation of the outputs of the bistable system(with different μ ). The results show that the self correlation will reach maximum when a sudden change of output occurs, and hence prove that SR is sensitive sharply to the change of the parameters μ , and also provide one novel method to express the outputs which hasnt been solved till now. The adaptive algorithm was also applied to analyze the weak Laser Raman spectrum of a CCl 4 sample(liquid in capillary) which was measured with SPEX 1403 Laser Raman spectrometer from 250 cm -1 to 418 cm -1 on 5 mW(output power of laser) . The spectrum was analyzed with the adaptive algorithm by varying the data to (-4 13, 3 50) and declining μ from 2 0 with step 0 01. The results obtained show that the adaptive algorithm was able to detect the weak signal automatically and correctly.
A novel method for extracting weak signal based on the theory of stochastic resonance was proposed. It was implemented by using the cooperative effect of noise instead of adding noise to a weak signal. The previous studies show that several disadvantages exist in the adding noise method. Due to the fact that adding noise to the weak signal will decline the signal-noise-radio（SNR） of the input of the nonlinear system, it will lower the detection effect. Additionally, the resonance point is determined manually, and also obvious offset of the peak position may occur in the result analyzed. Here the novel method was applied to analyze the weak laser-Raman spectrum of a CCl4 sample （liquid in capillary） which was measured with SPEX-1403 laser-Raman-spectrometer from 250 cm-1 to 418 cm-1 on 5 mW （output power of laser）. The spectrum was analyzed with the novel method by varying the data to [-4\^13, 3\^50] and declining μ from 2.0 and compared with the result acquired by wavelet analysis. The results show that the novel method can greatly increase the SNR of input signal easily to detect the weak signal. With the deep research of the theory of stochastic resonance and improvement of the new method, it will probably become a power tool to analyze spectrum.
