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A general architecture of a first order Hidden Markov Model. Each oval shape represents a random variable. The random variable x(t) is the hidden state at time t with an initial state x(0). The random variable e(t) is the observation (evidence) at time t. The arrows in the diagram indicate conditional probabilities.
