针对传统的支持向量机方法不能提供后验概率的输出问题，从信息熵的角度采用最大熵估计方法，直接对支持向量机输出进行后验概率建模。
To the problem that the standard SVM does not provide probabilities output, the probabilistic outputs for support vector machines is modeled based on the maximum entropy estimation.
最后，探讨了动态一致性检验的频谱(经典谱和最大熵谱)比较法，包括平稳序列频谱的估计和比较。
In the end, spectrum (classical spectrum and maximum entropy spectrum) comparative methods of dynamic consistency validation are discussed, including compare and estimation of stable series spectrum.
计算机模拟结果表明，改进的最大熵谱估计测向方法在很大程度上提高了测向的精度和分辨率。
Computer simulation results show that the modified method has some significant improvement over the original method in resolution and accuracy of bearing estimations.
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