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中文摘要：
为提高红外步态识别的效果，提出一种基于径向基函数神经网络的多分类器融合算法。对红外步态序列。分别应用基于轮廓线傅立叶描述子特征的模糊分类器和基于下肢关节角度特征的贝叶斯分类器进行识别，再利用径向基函数神经网络的学习和分类功能，对获得的输出信息进行度量层的融合和再识别。仿真实验结果表明。该算法获得更加精确的分类效果。
英文摘要：
Proposes the multiple classifier fusion algorithm based on radial basis function neural network in order to improve the effect of infrared gait recognition. The infrared gait sequences are recognized respectively by applying the fuzzy classifier based on Fourier descriptor characteristic of contour line and the Bayesian classifier based on the feature of lower limb joint angles, then fuses and recognizes the obtained output information in the measure layer by using the learning and sorting function of radial basis function neural network. Simulation result shows that this algorithm can achieve more accurate classification effect.
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