Modelling and inverting complex-valued Wiener systems

We develop a complex-valued (CV) B-spline neural network approach for efficient identification and inversion of CV Wiener systems. The CV nonlinear static function in the Wiener system is represented using the tensor product of two univariate B-spline neural networks. With the aid of a least squares parameter initialisation, the Gauss-Newton algorithm effectively estimates the model parameters that include the CV linear dynamic model coefficients and B-spline neural network weights. The identification algorithm naturally incorporates the efficient De Boor algorithm with both the B-spline curve and first order derivative recursions. An accurate inverse of the CV Wiener system is then obtained, in which the inverse of the CV nonlinear static function of the Wiener system is calculated efficiently using the Gaussian-Newton algorithm based on the estimated B-spline neural network model, with the aid of the De Boor recursions. The effectiveness of our approach for identification and inversion of CV Wiener systems is demonstrated using the application of digital predistorter design for high power amplifiers with memory

Complex-valued B-spline neural networks for modeling and inverting Hammerstein systems

Many communication signal processing applications involve modelling and inverting complex-valued (CV) Hammerstein systems. We develops a new CV B-spline neural network approach for efficient identification of the CV Hammerstein system and effective inversion of the estimated CV Hammerstein model. Specifically, the CV nonlinear static function in the Hammerstein system is represented using the tensor product from two univariate B-spline neural networks. An efficient alternating least squares estimation method is adopted for identifying the CV linear dynamic model’s coefficients and the CV B-spline neural network’s weights, which yields the closed-form solutions for both the linear dynamic model’s coefficients and the B-spline neural network’s weights, and this estimation process is guaranteed to converge very fast to a unique minimum solution. Furthermore, an accurate inversion of the CV Hammerstein system can readily be obtained using the estimated model. In particular, the inversion of the CV nonlinear static function in the Hammerstein system can be calculated effectively using a Gaussian-Newton algorithm, which naturally incorporates the efficient De Boor algorithm with both the B-spline curve and first order derivative recursions. The effectiveness of our approach is demonstrated using the application to equalisation of Hammerstein channels.

Electronic energy transfer in a dinuclear Ru/Os complex containing a photoresponsive dithienylethene derivative as bridging ligand

In order to build up a multicomponent system able to perform useful light-induced functions, a dithienylethene-bridged heterodinuclear metal complex (Ru/Os) has been prepared. The compound was characterized and its photophysical properties studied in detail.

A neural network enhanced generalized minimum variance self-tuning proportional, integral and derivative control algorithm for complex dynamic systems

A neural network enhanced proportional, integral and derivative (PID) controller is presented that combines the attributes of neural network learning with a generalized minimum-variance self-tuning control (STC) strategy. The neuro PID controller is structured with plant model identification and PID parameter tuning. The plants to be controlled are approximated by an equivalent model composed of a simple linear submodel to approximate plant dynamics around operating points, plus an error agent to accommodate the errors induced by linear submodel inaccuracy due to non-linearities and other complexities. A generalized recursive least-squares algorithm is used to identify the linear submodel, and a layered neural network is used to detect the error agent in which the weights are updated on the basis of the error between the plant output and the output from the linear submodel. The procedure for controller design is based on the equivalent model, and therefore the error agent is naturally functioned within the control law. In this way the controller can deal not only with a wide range of linear dynamic plants but also with those complex plants characterized by severe non-linearity, uncertainties and non-minimum phase behaviours. Two simulation studies are provided to demonstrate the effectiveness of the controller design procedure.

The domain derivative in rough-surface scattering and rigorous estimates for first-order perturbation theory

We investigate Fréchet differentiability of the scattered field with respect to variation in the boundary in the case of time–harmonic acoustic scattering by an unbounded, sound–soft, one–dimensional rough surface. We rigorously prove the differentiability of the scattered field and derive a characterization of the Fréchet derivative as the solution to a Dirichlet boundary value problem. As an application of these results we give rigorous error estimates for first–order perturbation theory, justifying small perturbation methods that have a long history in the engineering literature. As an application of our rigorous estimates we show that a plane acoustic wave incident on a sound–soft rough surface can produce an unbounded scattered field.

First-order turbulence closure for modelling complex canopy flows

Simple first-order closure remains an attractive way of formulating equations for complex canopy flows when the aim is to find analytic or simple numerical solutions to illustrate fundamental physical processes. Nevertheless, the limitations of such closures must be understood if the resulting models are to illuminate rather than mislead. We propose five conditions that first-order closures must satisfy then test two widely used closures against them. The first is the eddy diffusivity based on a mixing length. We discuss the origins of this approach, its use in simple canopy flows and extensions to more complex flows. We find that it satisfies most of the conditions and, because the reasons for its failures are well understood, it is a reliable methodology. The second is the velocity-squared closure that relates shear stress to the square of mean velocity. Again we discuss the origins of this closure and show that it is based on incorrect physical principles and fails to satisfy any of the five conditions in complex canopy flows; consequently its use can lead to actively misleading conclusions.

The acoustic signature of fluid flow in complex porous media

Effective medium approximations for the frequency-dependent and complex-valued effective stiffness tensors of cracked/ porous rocks with multiple solid constituents are developed on the basis of the T-matrix approach (based on integral equation methods for quasi-static composites), the elastic - viscoelastic correspondence principle, and a unified treatment of the local and global flow mechanisms, which is consistent with the principle of fluid mass conservation. The main advantage of using the T-matrix approach, rather than the first-order approach of Eshelby or the second-order approach of Hudson, is that it produces physically plausible results even when the volume concentrations of inclusions or cavities are no longer small. The new formulae, which operates with an arbitrary homogeneous (anisotropic) reference medium and contains terms of all order in the volume concentrations of solid particles and communicating cavities, take explicitly account of inclusion shape and spatial distribution independently. We show analytically that an expansion of the T-matrix formulae to first order in the volume concentration of cavities (in agreement with the dilute estimate of Eshelby) has the correct dependence on the properties of the saturating fluid, in the sense that it is consistent with the Brown-Korringa relation, when the frequency is sufficiently low. We present numerical results for the (anisotropic) effective viscoelastic properties of a cracked permeable medium with finite storage porosity, indicating that the complete T-matrix formulae (including the higher-order terms) are generally consistent with the Brown-Korringa relation, at least if we assume the spatial distribution of cavities to be the same for all cavity pairs. We have found an efficient way to treat statistical correlations in the shapes and orientations of the communicating cavities, and also obtained a reasonable match between theoretical predictions (based on a dual porosity model for quartz-clay mixtures, involving relatively flat clay-related pores and more rounded quartz-related pores) and laboratory results for the ultrasonic velocity and attenuation spectra of a suite of typical reservoir rocks. (C) 2003 Elsevier B.V. All rights reserved.

General derivative relations for anharmonic force fields

The brace notation, introduced by Allen and Csaszar (1993, J. chem. Phys., 98, 2983), provides a simple and compact way to deal with derivatives of arbitrary non-tensorial quantities. One of its main advantages is that it builds the permutational symmetry of the derivatives directly into the formalism. The brace notation is applied to formulate the general nth-order Cartesian derivatives of internal coordinates, and to provide closed forms for general, nth-order transformation equations of anharmonic force fields, expressed as Taylor series, from internal to Cartesian or normal coordinate spaces.

Development and application of in vivo expression technology (IVET) for analysing microbial gene expression in complex environments

Establishing the mechanisms by which microbes interact with their environment, including eukaryotic hosts, is a major challenge that is essential for the economic utilisation of microbes and their products. Techniques for determining global gene expression profiles of microbes, such as microarray analyses, are often hampered by methodological restraints, particularly the recovery of bacterial transcripts (RNA) from complex mixtures and rapid degradation of RNA. A pioneering technology that avoids this problem is In Vivo Expression Technology (IVET). IVET is a 'promoter-trapping' methodology that can be used to capture nearly all bacterial promoters (genes) upregulated during a microbe-environment interaction. IVET is especially useful because there is virtually no limit to the type of environment used (examples to date include soil, oomycete, a host plant or animal) to select for active microbial promoters. Furthermore, IVET provides a powerful method to identify genes that are often overlooked during genomic annotation, and has proven to be a flexible technology that can provide even more information than identification of gene expression profiles. A derivative of IVET, termed resolvase-IVET (RIVET), can be used to provide spatio-temporal information about environment-specific gene expression. More recently, niche-specific genes captured during an IVET screen have been exploited to identify the regulatory mechanisms controlling their expression. Overall, IVET and its various spin-offs have proven to be a valuable and robust set of tools for analysing microbial gene expression in complex environments and providing new targets for biotechnological development.

X-ray crystallographic study of DNA duplex cross-linking: simultaneous binding to two d(CGTACG)(2) molecules by a bis(9-aminoacridine-4-carboxamide) derivative

Acridine-4-carboxamides form a class of known DNA mono-intercalating agents that exhibit cytotoxic activity against tumour cell lines due to their ability to inhibit topoisomerases. Previous studies of bis-acridine derivatives have yielded equivocal results regarding the minimum length of linker necessary between the two acridine chromophores to allow bis-intercalation of duplex DNA. We report here the 1.7 angstrom resolution X-ray crystal structure of a six-carbon-linked bis(acridine-4-carboxamide) ligand bound to d(CGTACG)(2) molecules by non-covalent duplex cross-linking. The asymmetric unit consists of one DNA duplex containing an intercalated acridine-4-carboxamide chromophore at each of the two CG steps. The other half of each ligand is bound to another DNA molecule in a symmetry-related manner, with the alkyl linker threading through the minor grooves. The two crystallographically independent ligand molecules adopt distinct side chain interactions, forming hydrogen bonds to either O6 or N7 on the major groove face of guanine, in contrast to the semi-disordered state of mono-intercalators bound to the same DNA molecule. The complex described here provides the first structural evidence for the non-covalent cross-linking of DNA by a small molecule ligand and suggests a possible explanation for the inconsistent behaviour of six-carbon linked bis-acridines in previous assays of DNA bis-intercalation.

Design of a minimum variance multiple input-multiple output neuro self-tuning proportional-integral-derivative controller for non-linear dynamic systems

In this study a minimum variance neuro self-tuning proportional-integral-derivative (PID) controller is designed for complex multiple input-multiple output (MIMO) dynamic systems. An approximation model is constructed, which consists of two functional blocks. The first block uses a linear submodel to approximate dominant system dynamics around a selected number of operating points. The second block is used as an error agent, implemented by a neural network, to accommodate the inaccuracy possibly introduced by the linear submodel approximation, various complexities/uncertainties, and complicated coupling effects frequently exhibited in non-linear MIMO dynamic systems. With the proposed model structure, controller design of an MIMO plant with n inputs and n outputs could be, for example, decomposed into n independent single input-single output (SISO) subsystem designs. The effectiveness of the controller design procedure is initially verified through simulations of industrial examples.

Reduced-order modelling of a high-voltage oscillatory impulse generator

The design of high-voltage equipment encompasses the study of oscillatory surges caused by transients such as those produced by switching. By obtaining a model, the response of which reconstructs that observed in the actual system, simulation studies and critical tests can be carried out on the model rather than on the equipment itself. In this paper, methods for the construction of simplified models are described and it is shown how the use of a complex model does not necessarily result in superior response pattern reconstruction.

Fast regridding of large, complex geospatial datasets

In the earth sciences, data are commonly cast on complex grids in order to model irregular domains such as coastlines, or to evenly distribute grid points over the globe. It is common for a scientist to wish to re-cast such data onto a grid that is more amenable to manipulation, visualization, or comparison with other data sources. The complexity of the grids presents a significant technical difficulty to the regridding process. In particular, the regridding of complex grids may suffer from severe performance issues, in the worst case scaling with the product of the sizes of the source and destination grids. We present a mechanism for the fast regridding of such datasets, based upon the construction of a spatial index that allows fast searching of the source grid. We discover that the most efficient spatial index under test (in terms of memory usage and query time) is a simple look-up table. A kd-tree implementation was found to be faster to build and to give similar query performance at the expense of a larger memory footprint. Using our approach, we demonstrate that regridding of complex data may proceed at speeds sufficient to permit regridding on-the-fly in an interactive visualization application, or in a Web Map Service implementation. For large datasets with complex grids the new mechanism is shown to significantly outperform algorithms used in many scientific visualization packages.

Modeling of complex-valued Wiener systems using B-spline neural network

In this brief, a new complex-valued B-spline neural network is introduced in order to model the complex-valued Wiener system using observational input/output data. The complex-valued nonlinear static function in the Wiener system is represented using the tensor product from two univariate B-spline neural networks, using the real and imaginary parts of the system input. Following the use of a simple least squares parameter initialization scheme, the Gauss-Newton algorithm is applied for the parameter estimation, which incorporates the De Boor algorithm, including both the B-spline curve and the first-order derivatives recursion. Numerical examples, including a nonlinear high-power amplifier model in communication systems, are used to demonstrate the efficacy of the proposed approaches.

Spectro-electrochemical and DFT studies of a planar Cu(II)–phenolate complex active in the aerobic oxidation of primary alcohols

A square-planar compound [Cu(pyrimol)Cl] (pyrimol = 4-methyl-2-N-(2-pyridylmethylene)aminophenolate) abbreviated as CuL–Cl) is described as a biomimetic model of the enzyme galactose oxidase (GOase). This copper(II) compound is capable of stoichiometric aerobic oxidation of activated primary alcohols in acetonitrile/water to the corresponding aldehydes. It can be obtained either from Hpyrimol (HL) or its reduced/hydrogenated form Hpyramol (4-methyl-2-N-(2-pyridylmethyl)aminophenol; H2L) readily converting to pyrimol (L-) on coordination to the copper(II) ion. Crystalline CuL–Cl and its bromide derivative exhibit a perfect square-planar geometry with Cu–O(phenolate) bond lengths of 1.944(2) and 1.938(2) Å. The cyclic voltammogram of CuL–Cl exhibits an irreversible anodic wave at +0.50 and +0.57 V versus ferrocene/ferrocenium (Fc/Fc+) in dry dichloromethane and acetonitrile, respectively, corresponding to oxidation of the phenolate ligand to the corresponding phenoxyl radical. In the strongly donating acetonitrile the oxidation path involves reversible solvent coordination at the Cu(II) centre. The presence of the dominant CuII–L. chromophore in the electrochemically and chemically oxidised species is evident from a new fairly intense electronic absorption at 400–480 nm ascribed to a several electronic transitions having a mixed pi-pi(L.) intraligand and Cu–Cl -> L. charge transfer character. The EPR signal of CuL–Cl disappears on oxidation due to strong intramolecular antiferromagnetic exchange coupling between the phenoxyl radical ligand (L.) and the copper(II) centre, giving rise to a singlet ground state (S = 0). The key step in the mechanism of the primary alcohol oxidation by CuL–Cl is probably the alpha-hydrogen abstraction from the equatorially bound alcoholate by the phenoxyl moiety in the oxidised pyrimol ligand, Cu–L., through a five-membered cyclic transition state.