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In this paper, emph{diagnosability} is characterized for a labeled max-plus automaton $mathcal{A}^{mathcal{D}}$ over a dioid $mathcal{D}$ as a real-time system. In order to represent time elapsing, a special class of dioids called emph{progressive} are considered, in which there is a total canonical order, there is at least one element greater than $textbf{1}$, the product of sufficiently many elements greater than $textbf{1}$ is arbitrarily large, and the cancellative law is satisfied. Then a notion of diagnosability is formulated for $mathcal{A}^{mathcal{D}}$ over a progressive dioid $mathcal{D}$. By developing a notion of emph{concurrent composition}, a sufficient and necessary condition is given for diagnosability of automaton $mathcal{A}^{mathcal{D}}$. It is also proven that the problem of verifying diagnosability of $mathcal{A}^{underline{mathbb{Q}}}$ is coNP-complete, where coNP-hardness even holds for deterministic, deadlock-free, and divergence-free $mathcal{A}^{underline{mathbb{N}}}$, where $underline{mathbb{Q}}$ and $underline{mathbb{N}}$ are the max-plus dioids having elements in $mathbb{Q}cup{-infty}$ and $mathbb{N}cup{-infty}$, respectively.
In this paper, by developing appropriate methods, we for the first time obtain characterization of four fundamental notions of detectability for general labeled weighted automata over monoids (denoted by $mathcal{A}^{mathfrak{M}}$ for short), where t
We introduce the notion of adaptive synchronisation for pushdown automata, in which there is an external observer who has no knowledge about the current state of the pushdown automaton, but can observe the contents of the stack. The observer would th
We introduce homing vector automata, which are finite automata augmented by a vector that is multiplied at each step by a matrix determined by the current transition, and have to return the vector to its original setting in order to accept the input.
We introduce a certain restriction of weighted automata over the rationals, called image-binary automata. We show that such automata accept the regular languages, can be exponentially more succinct than corresponding NFAs, and allow for polynomial co
We present a new model of neural networks called Min-Max-Plus Neural Networks (MMP-NNs) based on operations in tropical arithmetic. In general, an MMP-NN is composed of three types of alternately stacked layers, namely linear layers, min-plus layers