提出用马尔科夫链蒙特卡罗(MCMC)方法来求解生物逆问题。导出待求参数分布规律的后验概率密度函数;采用自适应Metropolis算法构造Markov链;然后截取收敛的链序列计算数学期望,成功估计出未知参数。数值实验结果表明,该方法具有很高的估计精度和较好的抗噪声性能。
A new method is proposed to solve the biological inverse problem using Markov Chain Monte Carlo(MCMC) method.The, posterior probability density function of undetermined parameters is deduced.The adaptive Metropolis algorithm is used to construct the Markov chains.And the converged samples are used to calculate the mathematic expectation.So far, the unknown parameters of biological inverse problems are estimated successfully.The results of numerical experiments show that parameters estimated by the new method have high precision and the noise is filtered completely.