【摘要】 作者提出了一种新的方法来解决通过小波变换后的隐马尔可夫过程参数的计算问题.这个方法不必根据变换后的结果对系统参数进行重新估计,而只需利用变换后输出的小波系数直接来计算参数即可,避免了保留所有训练数据的繁琐复杂计算过程.更多还原

【Abstract】 In this paper, a new method to adapt the Hidden Markov Model (HMM) parameters is proposed when the original feature vector sequences extracted from handwritten characters are transformed by wavelet. By this method, readers are able to be free from the requirement of retraining the whole recognition parameters when the feature vectors are changed and makes it sufficient to adapt the parameters to the given impulse response of wavelet filter. The authors evaluate the performance of the proposed method, and compare it to that of the retrained HMM parameters based on the handwritten character recognition experiments.更多还原