Instrumental variable methods for system identification

This paper gives a tutorial overview of instrumental variable methods. Comparisons are made to the least-squares method. An analysis including consistency and asymptotic distribution of the parameter estimates is included.Work supported in part by Swedish Research Council for Engineering Sciences under contract 95-800, and the Foundation for Strategic Research.     

Study of Capon method for array signal processing

The mean-square error (MSE) of Capon estimate of the directions-of-arrival (DOA) is established in the narrowband array processing case. An improved Capon-like DOA estimator is proposed and its MSE is studied as well. Performance comparisons between the standard and improved Capon DOA estimates, and between these two estimates and the linear prediction DOA estimate, are performed. It is concluded that the improved Capon-like method introduced in this paper provides more accurate DOA estimates in most cases.This work has been supported by the Swedish Research Council for Engineering Sciences under contract 91–676.     

On the concentrated stochastic likelihood function in array signal processing

The stochastic likelihood function [(STO)LF] associated with the narrowband signal processing problem can be concentrated with respect to the signal covariance matrix elements and the noise power. Although this is a known fact, no clear-cut derivation of the concentrated (STO)LF appears to be available in the literature. In this short paper we provide a simple, complete proof of the concentrated (STO)LF formula.The work of A. Nehorai was supported by the Air Force Office of Scientific Research under Grant no. F49620-93-1-0096, the Office of Naval Research under Grant no. N00014-91-J-1298, and the National Science Foundation under grant no. MIP-9122753. The work of P. Stoica was supported by the Swedish Research Council for Engineering Sciences under contract no. 93-669.     

The effect of arginine on gold nanoparticles in colloidal solutions and in thin films

Gold nanoparticles were prepared in aqueous colloidal solutions and their interaction with L-arginine solutions at different concentrations was investigated by UV-vis spectroscopy, transmission electron microscopy (TEM) and atomic force microscopy (AFM). The shift towards red of the absorption maximum of gold nanoparticles with increasing L-arginine concentration and in time, and the apparition of a new large band at higher wavelength evidence the formation of assemblies of gold nanoparticles, mediated by the amino acid. TEM images present the progress in the building process of supermolecular structures. Further, the AFM images show the self assemblies of gold nanoparticles capped with L-arginine well ordered in large domains on silanized glass. As a model for the process, we suggest that the positively charged guanidinium group of L-arginine is anchored on the negative citrate capped gold nanoparticles, while the other two functionalities of L-arginine are involved in the bonding between gold nanoparticles. The ability of arginine to specifically bind gold nanoparticles could lead to an increased ability of proteins, containing arginine, to specifically bind to nanogold. Then, they bind other target proteins or different ligands underlying numerous biological and medical applications that range from nanoscale biosensors, cell-cell communications to targeted delivery of drugs to cancer cells.     

Sensitivity analysis of grating parameter estimation

An optimization method for the sensitivity of diffraction efficiency measurements is presented. I define the sensitivity as the estimation precision of the grating parameters. The optimization method called sensitivity analysis for fitting scans all the possible measurement configurations and selects the configuration that yields the best sensitivity. The scan is made over the domain of the experimental parameters of the arrangement, such as the azimuth angle of the grating and the orientation angles of the analyzer and the polarizer. These parameters can be freely varied, and among the multitude of possible combinations there is one configuration that provides optimum sensitivity. Comparison with experimental results reveals a qualitative agreement between theory and practice.     

HIGH-SPEED PCA ENCRYPTION ALGORITHM USING RECONFIGURABLE COMPUTING

In this work, an originally bio-inspired cryptosystem is developed. It is based on the use of cellular automata (CAs) as pseudorandom bit generators and programmable cellular automata (PCA) to construct the block ciphering functions of the proposed enciphering scheme. The cryptosystem is featured by resistance on different types of attacks and high speed due to the cellular automata's parallel information processing property. The proposed architecture could be efficiently implemented in reconfigurable hardware like field programmable gate arrays (FPGAs) and could be applied in high-speed data communication. The project was implemented in two experimental hardware platforms based on Spartan 3 XC3S400fg456-4 and XILINX Spartan 3E XC3S500E.     

Investigation of carbon nanofibers as support for bioactive substances

In this paper we have studied the adsorption properties of various bio-active systems onto the surface of carbon nanofibers (CNF) synthesized by chemical vapor deposition (CVD). Amino acids (alanine, aspartic acid, glutamic acid) and glucose oxidase (GOx) were adsorbed on CNF and the results were compared with those obtained when activated carbon (AC) was used as support. CNF and AC properties (hydrophilic or hydrophobic properties) were characterized by the pH value, the concentration of acidic/basic sites and by naphthalene adsorption. CNF with immobilized GOx was additionally investigated as a highly sensitive glucose biosensor. An amperometric method was used in an original manner to detect the changes in the specific activity of GOx, immobilized longer time on CNF. The method demonstrates that not the whole enzyme adsorbed onto CNF can catalyze the oxidation of glucose from the solution.     

3D High-resolution Mapping of Polarization Profiles in Thin Poly(vinylidenefluoride-trifluoroethylene) (PVDF-TrFE) Films Using Two Thermal Techniques

In this paper, two non-destructive thermal methods are used in order to determine, with a high degree of accuracy, three-dimensional polarization distributions in thin films (12 ?m) of poly(vinylidenefluoride-trifluoroethylene) (PVDF-TrFE). The techniques are the frequency-domain Focused Laser Intensity Modulation Method (FLIMM) and time-domain Thermal-Pulse Tomography (TPT). Samples were first metalized with grid-shaped electrode and poled. 3D polarization mapping yielded profiles which reproduce the electrode-grid shape. The polarization is not uniform across the sample thickness. Significant polarization values are found only at depths beyond 0.5 ?m from the sample surface. Both methods provide similar results, TPT method being faster, whereas the FLIMM technique has a better lateral resolution.     

Neural networks-based adaptive control for a class of nonlinear bioprocesses

The paper studies the design and analysis of a neural adaptive control strategy for a class of square nonlinear bioprocesses with incompletely known and time-varying dynamics. In fact, an adaptive controller based on a dynamical neural network used as a model of the unknown plant is developed. The neural controller design is achieved by using an input–output feedback linearization technique. The adaptation laws of neural network weights are derived from a Lyapunov stability property of the closed-loop system. The convergence of the system tracking error to zero is guaranteed without the need of network weights convergence. The resulted control method is applied in a depollution control problem in the case of a wastewater treatment bioprocess, belonging to the square nonlinear class, for which kinetic dynamics are strongly nonlinear, time varying and not exactly known.