Above are papers related to the following paper: [Paper_ID] Paper #1154074. 	[Title]  [Abstract] Report SYCON-93-09 Recent Results on Lyapunov-theoretic Techniques for Nonlinear Stability ABSTRACT This paper presents a Converse Lyapunov Function Theorem motivated by robust control analysis and design. Our result is based upon, but generalizes, various aspects of well-known classical theorems. In a unified and natural manner, it (1) includes arbitrary bounded disturbances acting on the system, (2) deals with global asymptotic stability, (3) results in smooth (infinitely differentiable) Lyapunov functions, and (4) applies to stability with respect to not necessarily compact invariant sets. As a corollary of the obtained Converse Theorem, we show that the well-known Lyapunov sufficient condition for "input-to-state stability" is also necessary, settling positively an open question raised by several authors during the past few years. Please summarise all the given information.

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Paper #1154074 has the title `nan` and the abstract `Report SYCON-93-09 Recent Results on Lyapunov-theoretic Techniques for Nonlinear Stability ABSTRACT This paper presents a Converse Lyapunov Function Theorem motivated by robust control analysis and design. Our result is based upon, but generalizes, various aspects of well-known classical theorems. In a unified and natural manner, it (1) includes arbitrary bounded disturbances acting on the system, (2) deals with global asymptotic stability, (3) results in smooth (infinitely differentiable) Lyapunov functions, and (4) applies to stability with respect to not necessarily compact invariant sets. As a corollary of the obtained Converse Theorem, we show that the well-known Lyapunov sufficient condition for "input-to-state stability" is also necessary, settling positively an open question raised by several authors during the past few years. 
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Question: Which category should Paper #1154074 be classified as ?
You can select one from ['Neural_Networks', 'Case_Based', 'Theory', 'Reinforcement_Learning', 'Probabilistic_Methods', 'Rule_Learning', 'Genetic_Algorithms'].


Paper #1154074 has the title `nan` and the abstract `Report SYCON-93-09 Recent Results on Lyapunov-theoretic Techniques for Nonlinear Stability ABSTRACT This paper presents a Converse Lyapunov Function Theorem motivated by robust control analysis and design. Our result is based upon, but generalizes, various aspects of well-known classical theorems. In a unified and natural manner, it (1) includes arbitrary bounded disturbances acting on the system, (2) deals with global asymptotic stability, (3) results in smooth (infinitely differentiable) Lyapunov functions, and (4) applies to stability with respect to not necessarily compact invariant sets. As a corollary of the obtained Converse Theorem, we show that the well-known Lyapunov sufficient condition for "input-to-state stability" is also necessary, settling positively an open question raised by several authors during the past few years. 
`.
Question: Which category should Paper #1154074 be classified as ?
You can select one from ['Neural_Networks', 'Case_Based', 'Theory', 'Reinforcement_Learning', 'Probabilistic_Methods', 'Rule_Learning', 'Genetic_Algorithms'].

This paper should be classified into: Neural_Networks