In this paper we present some new solutions for design space exploration of parameterized systems. The approaches use multi-objective optimisation techniques based on the concept of Pareto-optimality to determine the power/performance trade-off front for a highly parametric system-on-a-chip for digital camera applications. The approaches used are purely heuristic, genetic algorithm-based and a ...

In this paper we prove that the same design method of constant controllers for a delay systems given in the literature can be used to stabilize a minimum phase systems with nonlinearly correlated perturbations in the coefficients. This type of perturbation is induced by the composition with strictly positive real functions. This result can also be interpreted on the context of simultaneous and ...

We extend a systematic method for the derivation of high order schemes for affinely controlled nonlinear systems to a larger class of systems in which the control variables are allowed to appear nonlinearly in multiplicative terms. Using an adaptation of the stochastic Taylor expansion to control systems we construct Taylor schemes of arbitrary high order and indicate how derivative free Runge-...

The original and popular adaptive control theory usually deals with linear parameterizations (LP) of uncertainties, that is, it is assumed that uncertain quantities in dynamic systems are expressed linearly with respect to unknown parameters. Actually, most developed approaches such as gradient-based ones or recursive least squares [1, 2] rely heavily on this assumption and effective techniques...

A new method for gradient-based optimization of electromagnetic systems using parametric sensitivity macromodels is presented. Parametric macromodels accurately describe the parameterized frequency behavior of electromagnetic systems and their corresponding parameterized sensitivity responses with respect to design parameters, such as layout and substrate parameters. A set of frequency-dependen...

In this paper we present an automatic verification technique for parameterized systems where the subsystem behavior is modeled using the πcalculus. At its core, our technique treats each process instance in a system as a property transformer. Given a property φ that we want to verify of an N -process system, we use a partial model checker to infer the property φ′ (stated as a formula in a suffi...

We characterize the complexity of liveness verification for parameterized systems consisting of a leader process and arbitrarily many anonymous and identical contributor processes. Processes communicate through a shared, bounded-value register. While each operation on the register is atomic, there is no synchronization primitive to execute a sequence of operations atomically. We analyze the cas...

Dataflow has proven to be an attractive computation model for programming digital signal processing (DSP) applications. A restricted version of dataflow, termed synchronous dataflow (SDF), that offers strong compile-time predictability properties, but has limited expressive power, has been studied extensively in the DSP context. Many extensions to synchronous dataflow have been proposed to incr...

In recent years, it has been established that regular model checking can be successfully applied to several parameterized veriication problems. However, there are many parameterized veriication problems that cannot be described by regular languages, and thus cannot be veri-ed using regular model checking. In this study we try to practice symbolic model checking using classes of languages more e...

Many safety-critical systems that have been considered by the verification community are parameterized by the number of concurrent components in the system, and hence describe an infinite family of systems. Traditional model checking techniques can only be used to verify specific instances of this family. In this paper, we present a technique based on compositional model checking and program an...