Above are papers related to the following paper: [Paper_ID] Paper #1121569. 	[Title] A Characterization of Integral Input to State Stability [Abstract] Just as input to state stability (iss) generalizes the idea of finite gains with respect to supremum norms, the new notion of integral input to state stability (iiss) generalizes the concept of finite gain when using an integral norm on inputs. In this paper, we obtain a necessary and sufficient characterization of the iiss property, expressed in terms of dissipation inequalities. Please summarise all the given information.

Above are papers related to the following paper: [Paper_ID] Paper #103430. 	[Title] Input to State Stabilizability for Parameterized Families of Systems Key Words: Nonlinear stability, Robust control, [Abstract]  Please summarise all the given information.

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Paper #1121569 has the title `A Characterization of Integral Input to State Stability  
` and the abstract `Just as input to state stability (iss) generalizes the idea of finite gains with respect to supremum norms, the new notion of integral input to state stability (iiss) generalizes the concept of finite gain when using an integral norm on inputs. In this paper, we obtain a necessary and sufficient characterization of the iiss property, expressed in terms of dissipation inequalities. 
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Question: Which category should Paper #1121569 be classified as ?
You can select one from ['Neural_Networks', 'Case_Based', 'Theory', 'Reinforcement_Learning', 'Probabilistic_Methods', 'Rule_Learning', 'Genetic_Algorithms'].


Paper #1121569 has the title `A Characterization of Integral Input to State Stability  
` and the abstract `Just as input to state stability (iss) generalizes the idea of finite gains with respect to supremum norms, the new notion of integral input to state stability (iiss) generalizes the concept of finite gain when using an integral norm on inputs. In this paper, we obtain a necessary and sufficient characterization of the iiss property, expressed in terms of dissipation inequalities. 
`.
Question: Which category should Paper #1121569 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