Modeling of hybrid systems by piecewise decomposition

Piecewise linear models systems arise as mathematical models of systems in many practical applications, often from linearization for nonlinear systems. There are two main approaches of dealing with these systems according to their continuous or discrete-time aspects. We propose an approach which is based on the state transformation, more particularly the partition of the phase portrait in different regions where each subregion is modeled as a two-dimensional linear time invariant system. Then the Takagi-Sugeno model, which is a combination of local model is calculated. The simulation results show that the Alpha partition is well-suited for dealing with such a system

An Interval Intelligent-based Approach for Fault Detection and Modelling

Not considered in the analytical model of the plant, uncertainties always dramatically decrease the performance of the fault detection task in the practice. To cope better with this prevalent problem, in this paper we develop a methodology using Modal Interval Analysis which takes into account those uncertainties in the plant model. A fault detection method is developed based on this model which is quite robust to uncertainty and results in no false alarm. As soon as a fault is detected, an ANFIS model is trained in online to capture the major behavior of the occurred fault which can be used for fault accommodation. The simulation results understandably demonstrate the capability of the proposed method for accomplishing both tasks appropriately

Multiuser detection in a dynamic environment — Part II: Joint user identification and parameter estimation

The problem of jointly estimating the number, the identities, and the data of active users in a time-varying multiuser environment was examined in a companion paper (IEEE Trans. Information Theory, vol. 53, no. 9, September 2007), at whose core was the use of the theory of finite random sets on countable spaces. Here we extend that theory to encompass the more general problem of estimating unknown continuous parameters of the active-user signals. This problem is solved here by applying the theory of random finite sets constructed on hybrid spaces. We doso deriving Bayesian recursions that describe the evolution withtime of a posteriori densities of the unknown parameters and data.Unlike in the above cited paper, wherein one could evaluate theexact multiuser set posterior density, here the continuous-parameter Bayesian recursions do not admit closed-form expressions. To circumvent this difficulty, we develop numerical approximationsfor the receivers that are based on Sequential Monte Carlo (SMC)methods (“particle filtering”). Simulation results, referring to acode-divisin multiple-access (CDMA) system, are presented toillustrate the theory.

Sequential estimation of multipath MIMO-OFDM channels

Wireless “MIMO” systems, employing multiple transmit and receive antennas, promise a significant increase of channel capacity, while orthogonal frequency-division multiplexing (OFDM) is attracting a good deal of attention due to its robustness to multipath fading. Thus, the combination of both techniques is an attractive proposition for radio transmission. The goal of this paper is the description and analysis of a new and novel pilot-aided estimator of multipath block-fading channels. Typical models leading to estimation algorithms assume the number of multipath components and delays to be constant (and often known), while their amplitudes are allowed to vary with time. Our estimator is focused instead on the more realistic assumption that the number of channel taps is also unknown and varies with time following a known probabilistic model. The estimation problem arising from these assumptions is solved using Random-Set Theory (RST), whereby one regards the multipath-channel response as a single set-valued random entity.Within this framework, Bayesian recursive equations determine the evolution with time of the channel estimator. Due to the lack of a closed form for the solution of Bayesian equations, a (Rao–Blackwellized) particle filter (RBPF) implementation ofthe channel estimator is advocated. Since the resulting estimator exhibits a complexity which grows exponentially with the number of multipath components, a simplified version is also introduced. Simulation results describing the performance of our channel estimator demonstrate its effectiveness.

Sequential estimation of time-varying multipath channel for MIMO-OFDM systems

In this paper, we introduce a pilot-aided multipath channel estimator for Multiple-Input Multiple-Output (MIMO) Orthogonal Frequency Division Multiplexing (OFDM) systems. Typical estimation algorithms assume the number of multipath components and delays to be known and constant, while theiramplitudes may vary in time. In this work, we focus on the more realistic assumption that also the number of channel taps is unknown and time-varying. The estimation problem arising from this assumption is solved using Random Set Theory (RST), which is a probability theory of finite sets. Due to the lack of a closed form of the optimal filter, a Rao-Blackwellized Particle Filter (RBPF) implementation of the channel estimator is derived. Simulation results demonstrate the estimator effectiveness.

Forward induction and the excess capacity puzzle: An experimental investigation

While the theoretical industrial organization literature has long arguedthat excess capacity can be used to deter entry into markets, there islittle empirical evidence that incumbent firms effectively behave in thisway. Bagwell and Ramey (1996) propose a game with a specific sequence ofmoves and partially-recoverable capacity costs in which forward inductionprovides a theoretical rationalization for firm behavior in the field. Weconduct an experiment with a game inspired by their work. In our data theincumbent tends to keep the market, in contrast to what the forwardinduction argument of Bagwell and Ramey would suggest. The results indicatethat players perceive that the first mover has an advantage without havingto pre-commit capacity. In our game, evolution and learning do not driveout this perception. We back these claims with data analysis, atheoretical framework for dynamics, and simulation results.

Effects of differential taxation on factor accumulation and growth

In this paper we try to analyze the role of fiscal policy in fostering a higher participation of the different production factors in the human capital production sector in the long-run. Introducing a tax on physical capital and differentiating both a tax on raw labor wage and a tax on skills or human capital we also attempt to present a way to influence inequality as measured by the skill premium, thus trying to relate the increase in human capital with the decrease in income inequality. We will do that in the context of a non-scale growth model.The model here is capable to alter the shares of private factors devoted to each of the two production sectors, final output and human capital, and affect inequality in a different way according to the different tax changes. The simulation results derived in the paper show how a human capital (skills) tax cut, which could be interpreted as a reduction in progressivity, ends up increasing both the shares of labor and physical capital devoted to the production of knowledge and decreasing inequality. Moreover, a raw labor wage tax decrease, which could also be interpreted as an increase in the progressivity of the system, increases the share of labor devoted to the production of final output and increases inequality. Finally, a physical capital tax decrease reduces the share of physical capital devoted to the production of knowledge and allows for a lower inequality value. Nevertheless, none of the various types of taxes ends up changing the share of human capital in the knowledge production, which will deserve our future attention

Effects of differential taxation on factor accumulation and growth

In this paper we try to analyze the role of fiscal policy in fostering a higher participation of the different production factors in the human capital production sector in the long-run. Introducing a tax on physical capital and differentiating both a tax on raw labor wage and a tax on skills or human capital we also attempt to present a way to influence inequality as measured by the skill premium, thus trying to relate the increase in human capital with the decrease in income inequality. We will do that in the context of a non-scale growth model.The model here is capable to alter the shares of private factors devoted to each of the two production sectors, final output and human capital, and affect inequality in a different way according to the different tax changes. The simulation results derived in the paper show how a human capital (skills) tax cut, which could be interpreted as a reduction in progressivity, ends up increasing both the shares of labor and physical capital devoted to the production of knowledge and decreasing inequality. Moreover, a raw labor wage tax decrease, which could also be interpreted as an increase in the progressivity of the system, increases the share of labor devoted to the production of final output and increases inequality. Finally, a physical capital tax decrease reduces the share of physical capital devoted to the production of knowledge and allows for a lower inequality value. Nevertheless, none of the various types of taxes ends up changing the share of human capital in the knowledge production, which will deserve our future attention

Evaporation and coarsening dynamics with open boundaries

We present a study of the evaporation dynamics of a substance undergoing a coarsening process. The system is modeled by the Cahn-Hilliard equation with absorbing boundaries. We have found that the dynamics, although of a diffusive nature, is much slower than the usual one without coarsening. Analytical and simulation results are in reasonable agreement.

Front dynamics in the presence of spatio-temporal structured noises

Front dynamics modeled by a reaction-diffusion equation are studied under the influence of spatiotemporal structured noises. An effective deterministic model is analytical derived where the noise parameters, intensity, correlation time, and correlation length appear explicitly. The different effects of these parameters are discussed for the Ginzburg-Landau and Schlögl models. We obtain an analytical expression for the front velocity as a function of the noise parameters. Numerical simulation results are in a good agreement with the theoretical predictions.

Lattice-gas model of orientable molecules: Application to liquid crystals

We have analyzed a two-dimensional lattice-gas model of cylindrical molecules which can exhibit four possible orientations. The Hamiltonian of the model contains positional and orientational energy interaction terms. The ground state of the model has been investigated on the basis of Karl¿s theorem. Monte Carlo simulation results have confirmed the predicted ground state. The model is able to reproduce, with appropriate values of the Hamiltonian parameters, both, a smectic-nematic-like transition and a nematic-isotropic-like transition. We have also analyzed the phase diagram of the system by mean-field techniques and Monte Carlo simulations. Mean-field calculations agree well qualitatively with Monte Carlo results but overestimate transition temperatures.

Full complex Fresnel holograms displayed on liquid cristal displays

We propose a method to display full complex Fresnel holograms by adding the information displayed on two analogue ferroelectric liquid crystal spatial light modulators. One of them works in real-only configuration and the other in imaginary-only mode. The Fresnel holograms are computed by backpropagating an object at a selected distance with the Fresnel transform. Then, displaying the real and imaginary parts on each panel, the object is reconstructed at that distance from the modulators by simple propagation of light. We present simulation results taking into account the specifications of the modulators as well as optical results. We have also studied the quality of reconstructions using only real, imaginary, amplitude or phase information. Although the real and imaginary reconstructions look acceptable for certain distances, full complex reconstruction is always better and is required when arbitrary distances are used.

Analysis of the role of mobility-lifetime products in the performance of amorphous silicon p-i-n solar cells

An analytical model of an amorphous silicon p-i-n solar cell is presented to describe its photovoltaic behavior under short-circuit conditions. It has been developed from the analysis of numerical simulation results. These results reproduce the experimental illumination dependence of short-circuit resistance, which is the reciprocal slope of the I(V) curve at the short-circuit point. The recombination rate profiles show that recombination in the regions of charged defects near the p-i and i-n interfaces should not be overlooked. Based on the interpretation of the numerical solutions, we deduce analytical expressions for the recombination current and short-circuit resistance. These expressions are given as a function of an effective ¿¿ product, which depends on the intensity of illumination. We also study the effect of surface recombination with simple expressions that describe its influence on current loss and short-circuit resistance.

Generalized percolation in random directed networks

We develop a general theory for percolation in directed random networks with arbitrary two-point correlations and bidirectional edgesthat is, edges pointing in both directions simultaneously. These two ingredients alter the previously known scenario and open new views and perspectives on percolation phenomena. Equations for the percolation threshold and the sizes of the giant components are derived in the most general case. We also present simulation results for a particular example of uncorrelated network with bidirectional edges confirming the theoretical predictions.

Adsorption kinetics in the presence of external fields

In this article we present a detailed analysis of the kinetics of a class of sequential adsorption models that take into account the effect of externally applied fields (as an electric field, or a shear rate) on the adsorption. The excluded volume interactions related to the finite size of the adsorbing particles are modified by the external fields. As a result, new adsorption mechanisms appear with respect to the ones used to describe the kinetics in a quiescent fluid. In particular, if the adsorbing particles are allowed to roll over preadsorbed ones, adsorption becomes non local even in the simplest geometry. An exact analytic theory cannot be developed, but we introduce a self-consistent theory that turns out to agree with the simulation results over all the range of the parameters.