Information geometric measurements of generalisation

Neural networks can be regarded as statistical models, and can be analysed in a Bayesian framework. Generalisation is measured by the performance on independent test data drawn from the same distribution as the training data. Such performance can be quantified by the posterior average of the information divergence between the true and the model distributions. Averaging over the Bayesian posterior guarantees internal coherence; Using information divergence guarantees invariance with respect to representation. The theory generalises the least mean squares theory for linear Gaussian models to general problems of statistical estimation. The main results are: (1)~the ideal optimal estimate is always given by average over the posterior; (2)~the optimal estimate within a computational model is given by the projection of the ideal estimate to the model. This incidentally shows some currently popular methods dealing with hyperpriors are in general unnecessary and misleading. The extension of information divergence to positive normalisable measures reveals a remarkable relation between the dlt dual affine geometry of statistical manifolds and the geometry of the dual pair of Banach spaces Ld and Ldd. It therefore offers conceptual simplification to information geometry. The general conclusion on the issue of evaluating neural network learning rules and other statistical inference methods is that such evaluations are only meaningful under three assumptions: The prior P(p), describing the environment of all the problems; the divergence Dd, specifying the requirement of the task; and the model Q, specifying available computing resources.

Canonical solution groups of a homomorphism : manipulator kinematics, nonparametric regression and distributed object systems

The kinematic mapping of a rigid open-link manipulator is a homomorphism between Lie groups. The homomorphisrn has solution groups that act on an inverse kinematic solution element. A canonical representation of solution group operators that act on a solution element of three and seven degree-of-freedom (do!) dextrous manipulators is determined by geometric analysis. Seven canonical solution groups are determined for the seven do! Robotics Research K-1207 and Hollerbach arms. The solution element of a dextrous manipulator is a collection of trivial fibre bundles with solution fibres homotopic to the Torus. If fibre solutions are parameterised by a scalar, a direct inverse funct.ion that maps the scalar and Cartesian base space coordinates to solution element fibre coordinates may be defined. A direct inverse pararneterisation of a solution element may be approximated by a local linear map generated by an inverse augmented Jacobian correction of a linear interpolation. The action of canonical solution group operators on a local linear approximation of the solution element of inverse kinematics of dextrous manipulators generates cyclical solutions. The solution representation is proposed as a model of inverse kinematic transformations in primate nervous systems. Simultaneous calibration of a composition of stereo-camera and manipulator kinematic models is under-determined by equi-output parameter groups in the composition of stereo-camera and Denavit Hartenberg (DH) rnodels. An error measure for simultaneous calibration of a composition of models is derived and parameter subsets with no equi-output groups are determined by numerical experiments to simultaneously calibrate the composition of homogeneous or pan-tilt stereo-camera with DH models. For acceleration of exact Newton second-order re-calibration of DH parameters after a sequential calibration of stereo-camera and DH parameters, an optimal numerical evaluation of DH matrix first order and second order error derivatives with respect to a re-calibration error function is derived, implemented and tested. A distributed object environment for point and click image-based tele-command of manipulators and stereo-cameras is specified and implemented that supports rapid prototyping of numerical experiments in distributed system control. The environment is validated by a hierarchical k-fold cross validated calibration to Cartesian space of a radial basis function regression correction of an affine stereo model. Basic design and performance requirements are defined for scalable virtual micro-kernels that broker inter-Java-virtual-machine remote method invocations between components of secure manageable fault-tolerant open distributed agile Total Quality Managed ISO 9000+ conformant Just in Time manufacturing systems.

Flavones and related compounds as inhibitors of protein tyrosine kinases

Aberrant tyrosine protein kinase activity has been implicated in the formation and maintenance of malignancy and so presents a potential target for cancer chemotherapy. Quercetin, a naturally occuring flavonoid, inhibits the tyrosine protein kinase encoded by the Rous sarcoma virus but also exhibits many other effects. Analogues of this compound were synthesised by the acylation of suitable 2-hydroxyacetophenones with appropriately substituted aromatic (or alicyclic) acid chlorides, followed by base catalysed rearrangement to the 1-(2-hydroxyphenyl)-3-phenylpropan-1,3-diones. Acid catalysed ring closure furnished flavones. The majority of the 1-(2-hydroxyphenyl)-3-phenylpropan-1,3-diones were shown by NMR to exist in the enol form. This was supported by the crystal structure of 1-(2-hydroxy-4-methoxyphenyl)-3-phenylpropan-1,3-dione. In contrast, 1.(4,6-dimethoxy-2-hydroxyphenyl)-3-phenylpropan-1,3-dione did not exhibit keto-enol tautomerism in the NMR spectrum and was shown in its crystal structure to assume a twisted conformation. Assessment of the biological activity of the analogues of quercetin was carried out using whole cells and the kinase domain of the tyrosine protein kinase encoded by the Abelson murine leukaemia virus, ptab150 kinase. Single cell suspension cultures and clonogenic potential of murine fibroblasts transformed by the Abelson Murine leukaemia virus (ANN-1 cells) did not indicate the existence of any structure activity relationship required for cytotoxicity or cytostasis. No selective toxicity was apparent when the `normal' parent cell line, (3T3), was used to assess the cytotoxic potential of quercetin. The ICS50 for these compounds were generally in the region of 1-100M. The potential for these compounds to inhibit ptab150 kinase was determined. A definite substitution requirement emerged from these experiments indicating a necessity for substituents in the A ring or in the 3-position of the flavone nucleus. Kinetic data showed these inhibitors to be competitive for ATP.

The strength of column-to-foundation joints in reinforced concrete

This thesis is concerned with the experimental and theoretical investigation into the compression bond of column longitudinal reinforcement in the transference of axial load from a reinforced concrete column to a base. Experimental work includes twelve tests with square twisted bars and twenty four tests with ribbed bars. The effects of bar size, anchorage length in the base, plan area of the base, provision of bae tensile reinforcement, links around the column bars in the base, plan area of column and concrete compressive strength were investigated in the tests. The tests indicated that the strength of the compression anchorage of deformed reinforcing steel in the concrete was primarily dependent on the concrete strength and the resistance to bursting, which may be available within the anchorage . It was shown in the tests without concreted columns that due to a large containment over the bars in the foundation, failure occurred due to the breakdown of bond followed by the slip of the column bars along the anchorage length. The experimental work showed that the bar size , the stress in the bar, the anchorage length, provision of the transverse steel and the concrete compressive strength significantly affect the bond stress at failure. The ultimate bond stress decreases as the anchorage length is increased, while the ultimate bond stress increases with increasing each of the remainder parameters. Tests with concreted columns also indicated that a section of the column contributed to the bond length in the foundation by acting as an extra anchorage length. The theoretical work is based on the Mindlin equation( 3), an analytical method used in conjunction with finite difference calculus. The theory is used to plot the distribution of bond stress in the elastic and the elastic-plastic stage of behaviour. The theory is also used to plot the load-vertical displacement relationship of the column bars in the anchorage length, and also to determine the theoretical failure load of foundation. The theoretical solutions are in good agreement with the experimental results and the distribution of bond stress is shown to be significantly influenced by the bar stiffness factor K. A comparison of the experimental results with the current codes shows that the bond stresses currently used are low and in particular, CPIlO(56) specifies very conservative design bond stresses .

A Bayesian perspective on stochastic neurocontrol

Control design for stochastic uncertain nonlinear systems is traditionally based on minimizing the expected value of a suitably chosen loss function. Moreover, most control methods usually assume the certainty equivalence principle to simplify the problem and make it computationally tractable. We offer an improved probabilistic framework which is not constrained by these previous assumptions, and provides a more natural framework for incorporating and dealing with uncertainty. The focus of this paper is on developing this framework to obtain an optimal control law strategy using a fully probabilistic approach for information extraction from process data, which does not require detailed knowledge of system dynamics. Moreover, the proposed control method framework allows handling the problem of input-dependent noise. A basic paradigm is proposed and the resulting algorithm is discussed. The proposed probabilistic control method is for the general nonlinear class of discrete-time systems. It is demonstrated theoretically on the affine class. A nonlinear simulation example is also provided to validate theoretical development.

Reciprocating power generation in a chemically driven synthetic muscle

A scalable synthetic muscle has been constructed that transducts nanoscale molecular shape changes into macroscopic motion. The working material, which deforms affinely in response to a pH stimulus, is a self-assembled block copolymer comprising nanoscopic hydrophobic domains in a weak polyacid matrix. A device has been assembled where the muscle does work on a cantilever and the force generated has been measured. When coupled to a chemical oscillator this provides a free running chemical motor that generates a peak power of 20 mW kg 1 by the serial addition of 10 nm shape changes that scales over 5 orders of magnitude. It is the nanostructured nature of the gel that gives rise to the affine deformation and results in a robust working material for the construction of scalable muscle devices.

Antagonistic triblock polymer gels powered by pH oscillations

A study was conducted to create a pH-responsive layer, in which a small change in the individual polyacid or polybase gel length was transferred into a larger motion that curls up the gel. It was observed that the transfer of motion from a linear displacement into a curved displacement through the geometric design effectively increases the displacement rate. A robust, reversible, and chemically driven mechanical actuator was was produced that demonstrated its response over many pH oscillations. The affine nature of the triblock copolymers, demonstrated for for the polyacid and polybase indicated that the effect will also function at some smaller length scales, which is appropriate for a working biomimetic and soft nanotechnology device. The study also demonstrated the potential applicability of these polymeric gels and suggested the fabrication of related molecular machines and devices based on the principles of soft nanotechnology.

Autonomous volume transitions of a polybase triblock copolymer gel in a chemically driven pH-oscillator

A pH-responsive ABA triblock copolymer, comprising poly(methyl methacrylate)-b/ock-poly(2-(diethylamino)ethyl methacrylate)-block-poly(methyl methacrylate) [PMMA-b-PDEA-b-PMMA], has been cast Into thin films with a well-defined microstructure. Small Angle X-ray Scattering (SAXS) and Atomic Force Microscopy (AFM) studies confirm that this copolymer forms a hydrogel consisting of PMMA spheres embedded within a polybase PDEA matrix, with the PMMA domains acting as physical cross-links. The hydrogel has a pH-reversible coil-globule transition at around pH 4.5. This responsive physical property was exploited by immersing a sample of copolymer hydrogel in an aqueous solution containing a cyclic pH-oscillating reaction, whereby the pH was continuously oscillated above and below the transition pH so as to induce autonomous volume transitions. The changes in microscopic and macroscopic length scales correlate closely during (de)swelling cycles, with affine behaviour occurring over five orders of magnitude. Copyright © 2007 WILEY-VCH Verlag GmbH & Co. KGaA,.

A probabilistic indirect adaptive control for systems with input-dependent noise

A probabilistic indirect adaptive controller is proposed for the general nonlinear multivariate class of discrete time system. The proposed probabilistic framework incorporates input–dependent noise prediction parameters in the derivation of the optimal control law. Moreover, because noise can be nonstationary in practice, the proposed adaptive control algorithm provides an elegant method for estimating and tracking the noise. For illustration purposes, the developed method is applied to the affine class of nonlinear multivariate discrete time systems and the desired result is obtained: the optimal control law is determined by solving a cubic equation and the distribution of the tracking error is shown to be Gaussian with zero mean. The efficiency of the proposed scheme is demonstrated numerically through the simulation of an affine nonlinear system.

Self-affinity in financial asset returns

We test for departures from normal and independent and identically distributed (NIID) log returns, for log returns under the alternative hypothesis that are self-affine and either long-range dependent, or drawn randomly from an L-stable distribution with infinite higher-order moments. The finite sample performance of estimators of the two forms of self-affinity is explored in a simulation study. In contrast to rescaled range analysis and other conventional estimation methods, the variant of fluctuation analysis that considers finite sample moments only is able to identify both forms of self-affinity. When log returns are self-affine and long-range dependent under the alternative hypothesis, however, rescaled range analysis has higher power than fluctuation analysis. The techniques are illustrated by means of an analysis of the daily log returns for the indices of 11 stock markets of developed countries. Several of the smaller stock markets by capitalization exhibit evidence of long-range dependence in log returns. © 2012 Elsevier Inc. All rights reserved.