Above are papers related to the following paper: [Paper_ID] Paper #179706. 	[Title] Changing Supply Functions in Input/State Stable Systems [Abstract] We consider the problem of characterizing possible supply functions for a given dissipative nonlinear system, and provide a result that allows some freedom in the modification of such functions. Please summarise all the given information.

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 #7532. 	[Title] On Finite Gain Stabilizability of Linear Systems Subject to Input Saturation [Abstract] This paper deals with (global) finite-gain input/output stabilization of linear systems with saturated controls. For neutrally stable systems, it is shown that the linear feedback law suggested by the passivity approach indeed provides stability, with respect to every L p -norm. Explicit bounds on closed-loop gains are obtained, and they are related to the norms for the respective systems without saturation. These results do not extend to the class of systems for which the state matrix has eigenvalues on the imaginary axis with nonsimple (size &gt; 1) Jordan blocks, contradicting what may be expected from the fact that such systems are globally asymptotically stabilizable in the state-space sense; this is shown in particular for the double integrator. Please summarise all the given information.

Above are papers related to the following paper: [Paper_ID] Paper #7537. 	[Title] Global Stabilization of Linear Discrete-Time Systems with Bounded Feedback [Abstract] This paper deals with the problem of global stabilization of linear discrete time systems by means of bounded feedback laws. The main result proved is an analog of one proved for the continuous time case by the authors, and shows that such stabilization is possible if and only if the system is stabilizable with arbitrary controls and the transition matrix has spectral radius less or equal to one. The proof provides in principle an algorithm for the construction of such feedback laws, which can be implemented either as cascades or as parallel connections ("single hidden layer neural networks") of simple saturation functions. Please summarise all the given information.

Above are papers related to the following paper: [Paper_ID] Paper #141171. 	[Title] New Characterizations of Input to State Stability [Abstract] We present new characterizations of the Input to State Stability property. As a consequence of these results, we show the equivalence between the ISS property and several (apparent) variations proposed in the literature. Please summarise all the given information.

Above are papers related to the following paper: [Paper_ID] Paper #179702. 	[Title] FURTHER FACTS ABOUT INPUT TO STATE STABILIZATION "Further facts about input to state stabilization", IEEE [Abstract] Report SYCON-88-15 ABSTRACT Previous results about input to state stabilizability are shown to hold even for systems which are not linear in controls, provided that a more general type of feedback be allowed. Applications to certain stabilization problems and coprime factorizations, as well as comparisons to other results on input to state stability, are also briefly discussed. Please summarise all the given information.

Above are papers related to the following paper: [Paper_ID] Paper #75318. 	[Title] A Smooth Converse Lyapunov Theorem for Robust 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) allows arbitrary bounded time-varying parameters in the system description, (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. 1. Introduction. This work is motivated by problems of robust nonlinear stabilization. One of our main Please summarise all the given information.

Paper #179706 has the title `Changing Supply Functions in Input/State Stable Systems  
` and the abstract `We consider the problem of characterizing possible supply functions for a given dissipative nonlinear system, and provide a result that allows some freedom in the modification of such functions. 
`.
Question: Which category should Paper #179706 be classified as ?
You can select one from ['Neural_Networks', 'Case_Based', 'Theory', 'Reinforcement_Learning', 'Probabilistic_Methods', 'Rule_Learning', 'Genetic_Algorithms'].


Paper #179706 has the title `Changing Supply Functions in Input/State Stable Systems  
` and the abstract `We consider the problem of characterizing possible supply functions for a given dissipative nonlinear system, and provide a result that allows some freedom in the modification of such functions. 
`.
Question: Which category should Paper #179706 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