Two-stage mixed discrete-continuous identification of radial basis function (RBF) neural models for nonlinear systems

The identification of nonlinear dynamic systems using radial basis function (RBF) neural models is studied in this paper. Given a model selection criterion, the main objective is to effectively and efficiently build a parsimonious compact neural model that generalizes well over unseen data. This is achieved by simultaneous model structure selection and optimization of the parameters over the continuous parameter space. It is a mixed-integer hard problem, and a unified analytic framework is proposed to enable an effective and efficient two-stage mixed discrete-continuous; identification procedure. This novel framework combines the advantages of an iterative discrete two-stage subset selection technique for model structure determination and the calculus-based continuous optimization of the model parameters. Computational complexity analysis and simulation studies confirm the efficacy of the proposed algorithm.

Exploring the adoption and implementation of discrete and integrated IT systems: A Framework for analysis

Despite the substantial organisational benefits of integrated IT, the implementation of such systems – and particularly Enterprise Resource Planning (ERP) systems – has tended to be problematic, stimulating an extensive body of research into ERP implementation. This research has remained largely separate from the main IT implementation literature. At the same time, studies of IT implementation have generally adopted either a factor or process approach; both have major limitations. To address these imitations, factor and process perspectives are combined here in a unique model of IT implementation. We argue that • the organisational factors which determine successful implementation differ for integrated and traditional, discrete IT • failure to manage these differences is a major source of integrated IT failure. The factor/process model is used as a framework for proposing differences between discrete and integrated IT.

Operator systems from discrete groups

We express various sets of quantum correlations studied in the theoretical physics literature in terms of different tensor products of operator systems of discrete groups. We thus recover earlier results of Tsirelson and formulate a new approach for the study of quantum correlations. To do this we formulate a general framework for the study of operator systems arising from discrete groups. We study in detail the operator system of the free group Fn on n generators, as well as the operator systems of the free products of finitely many copies of the two-element group Z2. We examine various tensor products of group operator systems, including the minimal, the maximal, and the commuting tensor products. We introduce a new tensor product in the category of operator systems and formulate necessary and sufficient conditions for its equality to the commuting tensor product in the case of group operator systems.

Reuseable Silicon IP Cores for Discrete Wavelet Transform Applications

Architectures and methods for the rapid design of silicon cores for implementing discrete wavelet transforms over a wide range of specifications are described. These architectures are efficient, modular, scalable, and cover orthonormal and biorthogonal wavelet transform families. They offer efficient hardware utilization by exploiting a number of core wavelet filter properties and allow the creation of silicon designs that are highly parameterized, including in terms of wavelet type and wordlengths. Control circuitry is embedded within these systems allowing them to be cascaded for any desired level of decomposition without any interface glue logic. The time to produce chip designs for a specific wavelet application is typically less than a day and these are comparable in area and performance to handcrafted designs. They are also portable across a wide range of silicon foundries and suitable for field programmable gate array and programmable logic data implementation. The approach described has also been extended to wavelet packet transforms.

Wireless networked control systems with QoS-based sampling

Closing feedback loops using an IEEE 802.11b ad hoc wireless communication network incurs many challenges sensitivity to varying channel conditions and lower physical transmission rates tend to limit the bandwidth of the communication channel. Given that the bandwidth usage and control performance are linked, a method of adapting the sampling interval based on an 'a priori', static sampling policy has been proposed and, more significantly, assuring stability in the mean square sense using discrete-time Markov jump linear system theory. Practical issues including current limitations of the 802.11 b protocol, the sampling policy and stability are highlighted. Simulation results on a cart-mounted inverted pendulum show that closed-loop stability can be improved using sample rate adaptation and that the control design criteria can be met in the presence of channel errors and severe channel contention.

A discrete time-dependent method for metastable atoms and molecules in intense fields

The full-dimensional time-dependent Schrodinger equation for the electronic dynamics of single-electron systems in intense external fields is solved directly using a discrete method. Our approach combines the finite-difference and Lagrange mesh methods. The method is applied to calculate the quasienergies and ionization probabilities of atomic and molecular systems in intense static and dynamic electric fields. The gauge invariance and accuracy of the method is established. Applications to multiphoton ionization of positronium, the hydrogen atom and the hydrogen molecular ion are presented. At very high laser intensity, above the saturation threshold, we extend the method using a scaling technique to estimate the quasienergies of metastable states of the hydrogen molecular ion. The results are in good agreement with recent experiments. (C) 2004 American Institute of Physics.

Microscopic models for dielectric relaxation in disordered systems

It is shown how the Debye rotational diffusion model of dielectric relaxation of polar molecules (which may be described in microscopic fashion as the diffusion limit of a discrete time random walk on the surface of the unit sphere) may be extended to yield the empirical Havriliak-Negami (HN) equation of anomalous dielectric relaxation from a microscopic model based on a kinetic equation just as in the Debye model. This kinetic equation is obtained by means of a generalization of the noninertial Fokker-Planck equation of conventional Brownian motion (generally known as the Smoluchowski equation) to fractional kinetics governed by the HN relaxation mechanism. For the simple case of noninteracting dipoles it may be solved by Fourier transform techniques to yield the Green function and the complex dielectric susceptibility corresponding to the HN anomalous relaxation mechanism.

Assessment of the benefits of Discrete Conditional Survival Models in modelling ambulance response times

Many of the challenges faced in health care delivery can be informed through building models. In particular, Discrete Conditional Survival (DCS) models, recently under development, can provide policymakers with a flexible tool to assess time-to-event data. The DCS model is capable of modelling the survival curve based on various underlying distribution types and is capable of clustering or grouping observations (based on other covariate information) external to the distribution fits. The flexibility of the model comes through the choice of data mining techniques that are available in ascertaining the different subsets and also in the choice of distribution types available in modelling these informed subsets. This paper presents an illustrated example of the Discrete Conditional Survival model being deployed to represent ambulance response-times by a fully parameterised model. This model is contrasted against use of a parametric accelerated failure-time model, illustrating the strength and usefulness of Discrete Conditional Survival models.

Implementation of Discrete and Integrated IT: The Role of Organisational Structure and Culture

ntegrated organisational IT systems, such as enterprise resource planning (ERP), supply chain management (SCM) and digital manufacturing (DM), have promised and delivered substantial performance benefits to many adopting firms. However, implementations of such systems have tended to be problematic. ERP projects, in particular, are prone to cost and time overruns, not delivering anticipated benefits and often being abandoned before completion. While research has developed around IT implementation, this has focused mainly on standalone (or discrete), as opposed to integrated, IT systems. Within this literature, organisational (i.e., structural and cultural) characteristics have been found to influence implementation success. The key aims of this research are (a) to investigate the role of organisational characteristics in determining IT implementation success; (b) to determine whether their influence differs for integrated IT and discrete IT projects; and (c) to develop specific guidelines for managers of integrated IT implementations. An in-depth comparative case study of two IT projects was conducted within a major aerospace manufacturing company.

Discrete breathers in hexagonal dusty plasma lattices

The occurrence of single-site or multisite localized vibrational modes, also called discrete breathers, in two-dimensional hexagonal dusty plasma lattices is investigated. The system is described by a Klein-Gordon hexagonal lattice characterized by a negative coupling parameter epsilon in account of its inverse dispersive behavior. A theoretical analysis is performed in order to establish the possibility of existence of single as well as three-site discrete breathers in such systems. The study is complemented by a numerical investigation based on experimentally provided potential forms. This investigation shows that a dusty plasma lattice can support single-site discrete breathers, while three-site in phase breathers could exist if specific conditions, about the intergrain interaction strength, would hold. On the other hand, out of phase and vortex three-site breathers cannot be supported since they are highly unstable.

Discrete Conditional Phase-type models utilising classification trees: Application to modelling health service capacities

Discrete Conditional Phase-type (DC-Ph) models consist of a process component (survival distribution) preceded by a set of related conditional discrete variables. This paper introduces a DC-Ph model where the conditional component is a classification tree. The approach is utilised for modelling health service capacities by better predicting service times, as captured by Coxian Phase-type distributions, interfaced with results from a classification tree algorithm. To illustrate the approach, a case-study within the healthcare delivery domain is given, namely that of maternity services. The classification analysis is shown to give good predictors for complications during childbirth. Based on the classification tree predictions, the duration of childbirth on the labour ward is then modelled as either a two or three-phase Coxian distribution. The resulting DC-Ph model is used to calculate the number of patients and associated bed occupancies, patient turnover, and to model the consequences of changes to risk status.

Evaluating Train Protection Systems

This paper arose from the work carried out for the Cullen/Uff Joint Inquiry into Train Protection Systems. It is concerned with the problem of evaluating the benefits of safety enhancements in order to avoid rare, but catastrophic accidents, and the role of Operations Research in the process. The problems include both input values and representation of outcomes. A key input is the value of life. This paper briefly discusses why the value of life might vary from incident to incident and reviews alternative estimates before producing a 'best estimate' for rail. When the occurrence of an event is uncertain, the normal method is to apply a single 'expected' value. This paper argues that a more effective method of representing such situations is through Monte-Carlo simulation and demonstrates the use of the methodology on a case study of the decision as to whether or not advanced train protection (ATP) should have been installed on a route to the west of London. This paper suggests that the output is more informative than traditional cost-benefit appraisals or engineering event tree approaches. It also shows that, unlike the results from utilizing the traditional approach, the value of ATP on this route would be positive over 50% of the time.