Monitoring Temporal Properties of Continuous Signals

By Oded Maler, Dejan Nickovic. FORMATS/FTRTFT, 2004

1,458 citations recorded by the source corpus.

Subfields: Computational Theory and Mathematics, Hardware and Architecture, Software

View Paper: https://www.semanticscholar.org/paper/d7871c349ef0c2f8f22faa44b9f907340a426470

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Computational Theory and Mathematics

1. Dorsa Sadigh
2. Alexandre Donzé
3. Dimos V. Dimarogonas
4. Lars Lindemann
5. Sanjit A. Seshia
6. Sriram Sankaranarayanan
7. Ashish Kapoor
8. Georgios Fainekos

In Hardware and Architecture

1. Dorsa Sadigh
2. Alexandre Donzé
3. Ashish Kapoor
4. Georgios Fainekos
5. Dimos V. Dimarogonas
6. Lars Lindemann
7. Oded Maler
8. Sriram Sankaranarayanan

In Software

1. Alexandre Donzé
2. Dorsa Sadigh
3. Dimos V. Dimarogonas
4. Lars Lindemann
5. Sriram Sankaranarayanan
6. Ashish Kapoor
7. Georgios Fainekos
8. Oded Maler

Citations in the corpus

• Control Barrier Functions for Signal Temporal Logic Tasks (2019, methodology): “Signal temporal logic [7] is a predicate logic consisting of predicates μ that are obtained after evaluation of a predicate”
• A Roadmap Toward the Resilient Internet of Things for Cyber-Physical Systems (2018, background): “Signal Temporal Logic [116], [117] is a popular example of a real-time temporal logic suitable to reason about the real-time requirements for CPS which has been proposed for detection of threats [118].”
• Towards Verified Artificial Intelligence (2016, background): “Some initial steps have been taken with the use of logics with quantitative semantics, such as signal temporal logic [30], and automata-theoretic formalisms such as weighted automata [8], but much more remains to be done.”
• Model predictive control with signal temporal logic specifications (2014, background): “Signal Temporal Logic (STL) [22] was originally developed in order to specify and monitor the expected behavior of physical systems, including temporal constraints between events.”
• Safe Control under Uncertainty with Probabilistic Signal Temporal Logic (2016, background): “Given these statistical dependencies among the various variables, Bayesian inference techniques [31, 4, 2] aim to infer p(w|XL, tL) as a Gaussian distribution N (w; w̄,Σ).”
• A brief account of runtime verification (2009, background): “In [45,50] monitoring of continuous signals is considered, which is intrinsically different to observing discrete signals in a continuous time domain.”
• Robustness of temporal logic specifications for continuous-time signals (2009, background): “More recently, temporal logic testing [53] [40] has been proposed as a framework that can provide us with additional information about the properties of continuous or discrete-time signals.”
• Specification-Based Monitoring of Cyber-Physical Systems: A Survey on Theory, Tools and Applications (2018, methodology): “STL [96] extends the continuous-time Metric Temporal Logic (MTL) [87] with numerical predicates over real-valued variables.”
• Safe Control under Uncertainty (2015, background): “For example, Signal Temporal Logic (STL) [27] provides a framework for expressing real-valued dense-time temporal properties for safety, but assumes that the signal provided from the trajectory of the system is deterministically defined by the system dynamics.”
• Robust Satisfaction of Temporal Logic over Real-Valued Signals (2010, methodology): “With the flexibility of the definition of STL we can express a rich collection of relevant temporal properties for continuous signals.”