E. Solak, D. J. Leith, R. Murray-smith, W. E. Leithead, C. E. Rasmussen
Gaussian processes provide an approach to nonparametric modelling which allows a straightforward combination of function and derivative observations in an empirical model. This is of particular...
E. Solak, D. J. Leith, R. Murray-smith, W. E. Leithead, C. E. Rasmussen
Gaussian processes provide an approach to nonparametric modelling which allows a straightforward combination of function and derivative observations in an empirical model. This is of particular...
Instrumented usability analysis for mobile devices (2008)
Crossan, A., Murray-Smith, R., Brewster, S.A., Musizza, B.
No abstract available.
For a large data-set with groups of repeated measurements, a mixture model of Gaussian process priors is proposed for modelling the heterogeneity among the different replications. A hybrid Markov...
T. A. Johansen, R. Murray-smith
Dynamic Takagi-Sugeno fuzzy models are not always easy to interpret, in particular when they are identified from experimental data. Ideally, it is desirable that a dynamic Takagi-Sugeno fuzzy model...
E. Solak, R. Murray-smith, W. E. Leithead, D. J. Leith, C. E. Rasmussen
Gaussian processes provide an approach to nonparametric modelling which allows a straightforward combination of function and derivative observations in an empirical model. This is of particular...
Gaussian Process Functional Regression Modelling for Batch Data (2007)
Shi, J.Q., Wang, B., Murray-Smith, R., Titterington, D.M.
A Gaussian process functional regression model is proposed for the analysis of batch data. Covariance structure and mean structure are considered simultaneously, with the covariance structure modeled...
Show me the way to Monte Carlo: density-based trajectory navigation (2007)
Strachan, S., Williamson, J., Murray-Smith, R.
We demonstrate the use of uncertain prediction in a system for pedestrian navigation via audio with a combination of Global Positioning System data, a music player, inertial sensing, magnetic bearing...
BodySpace: inferring body pose for natural control of a music player (2007)
Strachan, S., Murray-Smith, R., O'Modhrain, S.
We describe the BodySpace system, which uses inertial sensing and pattern recognition to allow the gestural control of a music player by placing the device at different parts of the body. We...
Dynamics of tilt-based browsing on mobile devices (2007)
Cho, S.J., Choi, C., Sung, Y., Lee, K., Kim, Y.B., Murray-Smith, R.
A tilt-controlled photo browsing method for small mobile devices is presented. The implementation uses continuous inputs from an accelerometer, and a multimodal (visual, audio and vibrotactile)...
Devices as interactive physical containers: the shoogle system (2007)
Williamson, J., Murray-Smith, R., Hughes, S.
Shoogle is a novel interface for sensing data within a mobile device, such as presence and properties of text messages or remaining resources. It is based around active exploration: devices are...
A note on brain actuated spelling with the Berlin brain-computer interface (2007)
Blankertz, B., Krauledat, M., Dornhege, G., Williamson, J., Murray-Smith, R., Müller, K-R
Brain-Computer Interfaces (BCIs) are systems capable of decoding neural activity in real time, thereby allowing a computer application to be directly controlled by the brain. Since the...
J. Q. Shi, B. Wang, R. Murray-smith
Summary. A Gaussian process functional regression model is proposed for the analysis of batch data. Covariance structure and mean structure are considered simultaneously, with the covariance...
Inference of disjoint linear and nonlinear sub-domains of a nonlinear mapping (2006)
Leith, D.J., Leithead, W.E., Murray-Smith, R.
This paper investigates new ways of inferring nonlinear dependence from measured data. The existence of unique linear and nonlinear sub-spaces which are structural invariants of general nonlinear...
The Berlin Brain-Computer Interface presents the novel mental typewriter Hex-o-Spell (2006)
Blankertz, B., Dornhege, G., Krauledat, M., Schröder, M., Williamson, J., Murray-Smith, R., ...
We present a novel typewriter application "Hex-o-Spell" that is specifically tailored to the characteristics of direct brain-to-computer interaction. The high bandwidth at which a user may perceive...
It’s a long way to Monte-Carlo: probabilistic display in GPS navigation (2006)
Williamson, J., Strachan, S., Murray-Smith, R.
We present a mobile, GPS-based multimodal navigation system, equipped with inertial control that allows users to explore and navigate through an augmented physical space, incorporating and displaying...
Kamnik, R., Shi, J.Q., Murray-Smith, R., Bajd, T.
This paper presents analysis of the standing-up manoeuvre in paraplegia considering the body supportive forces as a potential feedback source in functional electrical stimulation (FES)-assisted...
Hierarchical Gaussian process mixtures for regression (2005)
Shi, J. Q., Murray-Smith, R., Titterington, D. M.
As a result of their good performance in practice and their desirable analytical properties, Gaussian process regression models are becoming increasingly of interest in statistics, engineering and...
Hex: dynamics and probabilistic text entry (2005)
Williamson, J., Murray-Smith, R.
We present a gestural interface for entering text on a mobile device via continuous movements, with control based on feedback from a probabilistic language model. Text is represented by continuous...
With the Gaussian Process model, the predictive distribution of the output corresponding to a new given input is Gaussian. But if this input is uncertain or noisy, the predictive distribution becomes...
Sonification of probabilistic feedback through granular synthesis (2005)
Williamson, J., Murray-Smith, R.
We describe a method to improve user feedback, specifically the display of time-varying probabilistic information, through asynchronous granular synthesis. We have applied these techniques to...
Hansen, J., Murray-Smith, R., Johansen, T.A.
Gaussian process prior models offer a nonparametric approach to modelling unknown nonlinear systems from experimental data. These are flexible models which automatically adapt their model complexity...
Rehabilitation robot cell for multimodal standing-up motion augmentation (2005)
Kamnik, R., Bajd, T., Williamson, J., Murray-Smith, R.
The paper presents a robot cell for multimodal standing-up motion augmentation. The robot cell is aimed at augmenting the standing-up capabilities of impaired or paraplegic subjects. The setup...
Human-human haptic collaboration in cyclical Fitts' tasks (2005)
Gentry, S., Feron, E., Murray-Smith, R.
Understanding how humans assist each other in haptic interaction teams could lead to improved robotic aids to solo human dextrous manipulation. Inspired by experiments reported in Reed et al. (2004),...
GpsTunes: controlling navigation via audio feedback (2005)
Strachan, S., Eslambolchilar, P., Murray-Smith, R., Hughes, S., O'Modhrain, S.
We combine the functionality of a mobile Global Positioning System (GPS) with that of an MP3 player, implemented on a PocketPC, to produce a handheld system capable of guiding a user to their desired...
Gait phase effects in mobile interaction (2005)
Crossan, A., Murray-Smith, R., Brewster, S.A., Kelly, J., Musizza, B.
One problem evaluating mobile and wearable devices is that they are used in mobile settings, making it hard to collect usability data. We present a study of tap-based selection of on-screen targets...
Self-tuning control of non-linear systems using gaussian process prior models (2005)
Sbarbaro, D., Murray-Smith, R.
Gaussian Process prior models, as used in Bayesian non-parametric statistical models methodology are applied to implement a nonlinear adaptive control law. The expected value of a quadratic cost...
Filtered gaussian processes for learning with large data-sets (2005)
Shi, J.Q., Murray-Smith, R., Titterington, D.M., Pearlmutter, B.A.
Kernel-based non-parametric models have been applied widely over recent years. However, the associated computational complexity imposes limitations on the applicability of those methods to problems...
Nonlinear predictive control with a gaussian process model (2005)
Gaussian process models provide a probabilistic non-parametric modelling approach for black-box identification of nonlinear dynamic systems. The Gaussian processes can highlight areas of the input...
Dynamic primitives for gestural interaction (2004)
Strachan, S., Murray-Smith, R., Oakley, I., Angesleva, J.
We describe the implementation of an interaction technique which allows users to store and retrieve information and computational functionality on different parts of their body. We present a dynamic...
Tilt-based automatic zooming and scaling in mobile devices â A state-space implementation (2004)
Eslambolchilar, P., Murray-Smith, R.
We provide a dynamic systems interpretation of the coupling of internal states involved in speed-dependent automatic zooming, and test our implementation on a text browser on a Pocket PC instrumented...
Variability in wrist-tilt accelerometer based gesture interfaces (2004)
In this paper we describe a study that examines human performance in a tilt control targeting task on a PDA. A three-degree of freedom accelerometer attached to the base of the PDA allows users to...
Haptic granular synthesis: targeting, visualisation and texturing (2004)
Crossan, A., Williamson, J., Murray-Smith, R.
This work introduces the idea of haptic rendering using granular synthesis - an established technique for synthesising audio. It describes the technique along with potential application areas, and...
Gaussian process model based predictive control (2004)
Kocijan, J., Murray-Smith, R., Rasmussen, C.E., Girard, A.
Gaussian process models provide a probabilistic non-parametric modelling approach for black-box identification of non-linear dynamic systems. The Gaussian processes can highlight areas of the input...
Granular synthesis for display of time-varying probability densities (2004)
Williamson, J., Murray-Smith, R.
We present a method for displaying time-varying probabilistic information to users using an asynchronous granular synthesis technique. We extend the basic synthesis technique to include distribution...
Model-based target sonification on mobile devices (2004)
Eslambolchilar, P., Crossan, A., Murray-Smith, R.
We investigate the use of audio and haptic feedback to augment the display of a mobile device controlled by tilt input. We provide an example of this based on Doppler effects, which highlight the...
Pointing without a pointer (2004)
Williamson, J., Murray-Smith, R.
We present a method for performing selection tasks based on continuous control of multiple, competing agents who try to determine the user's intentions from their control behaviour without requiring...
Haptic dancing: human performance at haptic decoding with a vocabulary (2003)
The inspiration for this study is the observation that swing dancing involves coordination of actions between two humans that can be accomplished by pure haptic signaling. This study implements a...
Adaptive, cautious, predictive control with Gaussian process priors (2003)
Murray-Smith, R., Sbarbaro, D., Rasmussen, C.E., Girard, A.
Nonparametric Gaussian Process models, a Bayesian statistics approach, are used to implement a nonlinear adaptive control law. Predictions, including propagation of the state uncertainty are made...
Girard, A., Rasmussen, C.E., Quinonero-Candela, J., Murray-Smith, R.
We consider the problem of multi-step ahead prediction in time series analysis using the non-parametric Gaussian process model. k-step ahead forecasting of a discrete-time non-linear dynamic system...
Derivative observations in Gaussian Process models of dynamic systems (2003)
Solak, E., Murray-Smith, R., Leithead, W.E., Leith, D.J., Rasmussen, C.E.
Gaussian processes provide an approach to nonparametric modelling which allows a straightforward combination of function and derivative observations in an empirical model. This is of particular...
Divide and conquer identification using Gaussian process priors (2002)
Leith, D. J., Leithead, W. E., Solak, E., Murray-Smith, R.
We investigate the reconstruction of nonlinear systems from locally identified linear models. It is well known that the equilibrium linearisations of a system do not uniquely specify the global...
Nonlinear adaptive control using non-parametric Gaussian Process prior models (2002)
Murray-Smith, R., Sbarbaro, D.
Nonparametric Gaussian Process prior models, taken from Bayesian statistics methodology are used to implement a nonlinear adaptive control law. The expected value of a quadratic cost function is...
Bayesian Regression and Classification Using (2002)
Mixtures Of Gaussian, J. Q. Shi, R. Murray-smith
For a large data-set with groups of repeated measurements, a mixture model of Gaussian process priors is proposed for modelling the heterogeneity among the different replications. A hybrid Markov...
Hierarchical Gaussian process mixtures for regression (2002)
J. Q. Shi, R. Murray-smith, D. M. Titterington
As a result of their good performance in practice and their desirable analytical properties, Gaussian process regression models are becoming increasingly of interest in statistics, engineering and...
Gaussian Process priors with ARMA noise models (2001)
We extend the standard covariance function used in the Gaussian Process prior nonparametric modelling approach to include correlated (ARMA) noise models. The improvement in performance is illustrated...
Gaussian Process Priors with ARMA Noise Models (2001)
Murray-Smith And Girard, R. Murray-smith, A. Girard
We extend the standard covariance function used in the Gaussian Process prior nonparametric modelling approach to include correlated (ARMA) noise models. The improvement in performance is illustrated...
On the interpretation and identification of dynamic Takagi-Sugenofuzzy models (2000)
Johansen, T.A., Shorten, R., Murray-Smith, R.
Dynamic Takagi-Sugeno fuzzy models are not always easy to interpret, in particular when they are identified from experimental data. It is shown that there exists a close relationship between dynamic...
Murray-Smith, R., Johansen, T. A., Shorten, R.
The use of multiple-model techniques has been reported in a variety of control and signal processing applications. However, several theoretical analyses have recently appeared which outline...
Robot docking using mixtures of Gaussians (1999)
Williamson, M., Murray-Smith, R., Hansen, V.
This paper applies the Mixture of Gaussians probabilistic model, combined with Expectation Maximization optimization to the task of summarizing three dimensionals range data for the mobile robot....
Modelling human control behaviour with a Markov-chain switched bank of control laws (1998)
A probabilistic model of human control behaviour is described. It assumes that human behaviour can be represented by switching among a number of relatively simple behaviours. The model structure is...
Hunt, K.J., Haas, R., Murray-Smith, R.
We establish the functional equivalence of a generalized class of Gaussian radial basis function (RBFs) networks and the full Takagi-Sugeno model (1983) of fuzzy inference. This generalizes an...
Local model architectures for nonlinear modelling and control (1995)
No abstract available.
Dimensionality Reduction in Basis-function Networks: Exploiting the link with fuzzy system (1994)
K.J. Hunt, R. Haas, R. Murray-Smith, Daimler-benz Ag
We address the dimensionality problem in the training of basis function networks of various types. Some results which establish the functional equivalence of basis function networks and fuzzy...
Combining case based reasoning with neural networks (1993)
This paper presents a neural network based technique for mapping problem situations to problem solutions for Case-Based Reasoning (CBR) applications. Both neural networks and CBR are instance-based...
Neural networks for modelling and control of a non-linear dynamic system (1992)
Murray-Smith, R., Neumerkel, D., Sbarbaro-Hofer, D.
The authors describe the use of neural nets to model and control a nonlinear second-order electromechanical model of a drive system with varying time constants and saturation effects. A model...