hmm hidden markov models 隐马尔可夫模型
The use of hidden Markov models (HMM) for faces is motivated by their partial invariance to variations in scaling and by the structure of faces.
隐马尔可夫模型(HMM)在人脸识别中的运用是由HMM在图像定标变化过程中的局部恒定性和人脸的结构所决定的。
Presents a new hybrid framework of hidden Markov models (HMM) and radial basis function (RBF) neural networks for speech recognition.
提出了一种隐马尔可夫模型（HMM）和径向基函数神经网络（RBF）相结合的语音识别新方法。
To enable hidden Markov models to account for dependencies between non-adjacent observation symbols, time-delay is introduced to standard high order HMM states.
为使得隐马尔可夫模型（HMM）能够处理非相邻可见符号之间的依赖关系，将延时机制引入标准的HMM中。
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