In order to improve the recognition rate of traffic signs’Chinese characters, we propose a mixed optimized deep Boltzmann machine(MDBM) algorithm to improve the approximation of probability distribution. Two sampling methods (grayscale sampling initialization and binary sampling initialization) are proposed to construct the restricted Boltzmann machines, which are overlapped to form the depth Boltzmann machine.  In addition, we propose a fine-tuning algorithm, called complex conjugate gradient method, to improve the fine-tuning part in deep Boltzmann machine. Experiments on traffic signs data show that the recognition rate of the proposed algorithm is better than that of the original deep Boltzmann machine.

 

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