A tutorial on hidden Markov models and selected applications in speech recognition
Readings in speech recognition
An introduction to symbolic dynamics and coding
An introduction to symbolic dynamics and coding
The theory of trackability with applications to sensor networks
ACM Transactions on Sensor Networks (TOSN)
The theory of trackability and robustness for process detection
The theory of trackability and robustness for process detection
IEEE Transactions on Information Theory
Error bounds for convolutional codes and an asymptotically optimum decoding algorithm
IEEE Transactions on Information Theory
Observability of Boolean networks: A graph-theoretic approach
Automatica (Journal of IFAC)
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An edge-colored directed graph is observable if an agent that moves along its edges from node to node is able to determine his position in the graph after a sufficiently long observation of the edge colors, and without accessing any information about the traversed nodes. When the agent is able to determine his position only from time to time, the graph is said to be partly observable. Observability in graphs is desirable in situations where autonomous agents are moving on a network and they want to localize themselves with limited information. In this paper, we completely characterize observable and partly observable graphs and show how these concepts relate to other concepts in the literature. Based on these characterizations, we provide polynomial time algorithms to decide observability, to decide partial observability, and to compute the minimal number of observations necessary for finding the position of an agent. In particular we prove that in the worst case this minimal number of observations increases quadratically with the number of nodes in the graph. We then consider the more difficult question of assigning colors to a graph so as to make it observable and we prove that two different versions of this problem are NP-complete.