Literature on methods for analysing interindustry interdependence and geographical concentration of firms began to multiply since the 1990s. The aim of this paper was to systematize the literature on methods and measu...
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Literature on methods for analysing interindustry interdependence and geographical concentration of firms began to multiply since the 1990s. The aim of this paper was to systematize the literature on methods and measures applied to the analysis of industrial clusters, as well as to identify trends in this knowledge field. The method used was bibliometrics, which consisted of a frequency evaluation of the publications and the relationship network between them. It was verified an exponential increase in the number of papers that composed this area, based mainly on the theories of New Economic Geography. Recently, the literature has focused on the geographic location in relation to interindustry linkages, and the frontier of knowledge has shifted from traditional methods of regional science to areas such as spatial statistics, econophysics and artificial intelligence. There are still relevant questions being explored, as Modifiable Area Unit Problem (aggregation bias), nevertheless, spatial anisotropy (directional bias) is still neglected and indicates a new research path.
The relationship between two gap metrics is investigated for a class of time-varying linear systems. Specifically, systems are considered to be causal linear maps between finite-energy continuous-time signals of nonun...
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The relationship between two gap metrics is investigated for a class of time-varying linear systems. Specifically, systems are considered to be causal linear maps between finite-energy continuous-time signals of nonuniformly lower-bounded support, and by definition, the corresponding input-output graphs admit normalized so-called strong-right and strong-left representations. First, a time-varying generalization of Vinnicombe's nu-gap is revisited to rectify an omission in the original developments and to verify compliance with the axioms of a metric. Subsequently, it is shown that this generalized nu-gap metric induces the same topology as an apposite adaptation of Feintuch's time-varying gap metric for discrete-time systems defined over finite-energy signals of uniformly lower-bounded support. The two generalized metrics are therefore qualitatively equivalent in robust stability analysis for linear time-varying feedback interconnections. Quantitatively, the nu-gap between a given pair of systems is never larger in value than the Feintuch gap.
Conic relations of an input-output system are important system properties that can be exploited in order to design robust controllers. Therefore, we study the problem of determining the minimal cone containing such an...
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Conic relations of an input-output system are important system properties that can be exploited in order to design robust controllers. Therefore, we study the problem of determining the minimal cone containing such an input-output system. While in applications the input-output relation itself is often undisclosed, input-output data tuples can be sampled. Therefore, we present an iterative sampling approach to determine conic relations of a linear time-invariant system from input-output data. This sampling approach is based on saddle-point dynamics, whose convergence properties are then investigated. (C) 2018, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved.
Knowledge of a dissipation inequality can disclose valuable system properties relevant for controller design. Therefore, we consider the problem of determining a dissipation inequality for an input-output system. In p...
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Knowledge of a dissipation inequality can disclose valuable system properties relevant for controller design. Therefore, we consider the problem of determining a dissipation inequality for an input-output system. In p...
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Knowledge of a dissipation inequality can disclose valuable system properties relevant for controller design. Therefore, we consider the problem of determining a dissipation inequality for an input-output system. In practice, yet, the core issue is that one would only know finitely many input-output samples while the input-output relationship would be undisclosed analytically. For such scenarios, we provide an approach for computing dissipation inequalities based upon knowledge of large amounts of input-output samples, as they arise in applications nowadays gathered under the term "big data". Our approach will, under certain conditions, provide dissipation inequalities which remain satisfied for all input-output pairs that the system can produce, though only having been derived from finitely many of them. (C) 2017, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved.
A universal adaptive controller is constructed that achieves asymptotic tracking of a given class of reference signals and asymptotic rejection of a prescribed set of disturbance signals for a class of multivariable i...
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A universal adaptive controller is constructed that achieves asymptotic tracking of a given class of reference signals and asymptotic rejection of a prescribed set of disturbance signals for a class of multivariable infinite-dimensional systems that are stabilizable by high-gain output feedback. The controller does not require an explicit identification of the system parameters or the injection of a probing signal. In contrast to most of the work in universal adaptive control, this paper is based on an input-output approach and the results do not require a state-space representation of the plant. The abstract input-output results are applied to retarded systems and integrodifferential systems.
The revised 1993 System of National Accounts (SNA) contains a chapter on social accounting matrices (SAMs), demonstrating that the input-output approach should be extended to a matrix presentation of a wider set of na...
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The application of functional analytic methods to the stability of feedback control systems with nonlinear, imprecise or unknown models is discussed. A method is proposed to find the appropiate center and radius param...
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The application of functional analytic methods to the stability of feedback control systems with nonlinear, imprecise or unknown models is discussed. A method is proposed to find the appropiate center and radius parameters of the Conicity Stability Criterion. A technique is also presented to deal with unmodelled plants and to obtain its functional gain in an empirical way from energy measures.
The application of functional analytic methods to the stability of feedback control systems with nonlinear, imprecise or unknown models is discussed. A method is proposed to find the appropiate center and radius param...
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The application of functional analytic methods to the stability of feedback control systems with nonlinear, imprecise or unknown models is discussed. A method is proposed to find the appropiate center and radius parameters of the Conicity Stability Criterion. A technique is also presented to deal with unmodelled plants and to obtain its functional gain in an empirical way from energy measures.
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