A theorem which shows that the local maximum found by the forward-backward algorithm in the case of discrete hidden Markov models is really local is presented. By this it is meant that this local maximum is restricted to lie in the same connected component of the set (x:P(x)展开▼
机译：提出了一个定理，该定理表明在离散隐马尔可夫模型的情况下，由前向后算法找到的局部最大值实际上是局部的。由此意味着，该局部最大值被限制为与初始点x / sub 0 /（）位于集合的相同连接分量（x：P（x）展开▼
