The Supervised IBP: Neighbourhood Preserving Infinite Latent Feature Models

We propose a probabilistic model to infer supervised latent variables in the Hamming space from observed data. Our model allows simultaneous inference of the number of binary latent variables, and their values. The latent variables preserve neighbourhood structure of the data in a sense that objects in the same semantic concept have similar latent values, and objects in different concepts have dissimilar latent values. We formulate the supervised infinite latent variable problem based on an intuitive principle of pulling objects together if they are of the same type, and pushing them apart if they are not. We then combine this principle with a flexible Indian Buffet Process prior on the latent variables. We show that the inferred supervised latent variables can be directly used to perform a nearest neighbour search for the purpose of retrieval. We introduce a new application of dynamically extending hash codes, and show how to effectively couple the structure of the hash codes with continuously growing structure of the neighbourhood preserving infinite latent feature space.

Multilinear function factorisation for time series feature extraction

This work applies a variety of multilinear function factorisation techniques to extract appropriate features or attributes from high dimensional multivariate time series for classification. Recently, a great deal of work has centred around designing time series classifiers using more and more complex feature extraction and machine learning schemes. This paper argues that complex learners and domain specific feature extraction schemes of this type are not necessarily needed for time series classification, as excellent classification results can be obtained by simply applying a number of existing matrix factorisation or linear projection techniques, which are simple and computationally inexpensive. We highlight this using a geometric separability measure and classification accuracies obtained though experiments on four different high dimensional multivariate time series datasets. © 2013 IEEE.

Motor learning of novel dynamics is not represented in a single global coordinate system: evaluation of mixed coordinate representations and local learning.

Successful motor performance requires the ability to adapt motor commands to task dynamics. A central question in movement neuroscience is how these dynamics are represented. Although it is widely assumed that dynamics (e.g., force fields) are represented in intrinsic, joint-based coordinates (Shadmehr R, Mussa-Ivaldi FA. J Neurosci 14: 3208-3224, 1994), recent evidence has questioned this proposal. Here we reexamine the representation of dynamics in two experiments. By testing generalization following changes in shoulder, elbow, or wrist configurations, the first experiment tested for extrinsic, intrinsic, or object-centered representations. No single coordinate frame accounted for the pattern of generalization. Rather, generalization patterns were better accounted for by a mixture of representations or by models that assumed local learning and graded, decaying generalization. A second experiment, in which we replicated the design of an influential study that had suggested encoding in intrinsic coordinates (Shadmehr and Mussa-Ivaldi 1994), yielded similar results. That is, we could not find evidence that dynamics are represented in a single coordinate system. Taken together, our experiments suggest that internal models do not employ a single coordinate system when generalizing and may well be represented as a mixture of coordinate systems, as a single system with local learning, or both.

Tandem system adaptation using multiple linear feature transforms

Adaptation to speaker and environment changes is an essential part of current automatic speech recognition (ASR) systems. In recent years the use of multi-layer percpetrons (MLPs) has become increasingly common in ASR systems. A standard approach to handling speaker differences when using MLPs is to apply a global speaker-specific constrained MLLR (CMLLR) transform to the features prior to training or using the MLP. This paper considers the situation when there are both speaker and channel, communication link, differences in the data. A more powerful transform, front-end CMLLR (FE-CMLLR), is applied to the inputs to the MLP to represent the channel differences. Though global, these FE-CMLLR transforms vary from time-instance to time-instance. Experiments on a channel distorted dialect Arabic conversational speech recognition task indicates the usefulness of adapting MLP features using both CMLLR and FE-CMLLR transforms. © 2013 IEEE.

Local lifetime engineering in 600V pin diode using mix-mode simulation

This paper reports a detailed analysis of the effect of local lifetime killing (LLK) within the drift region on the reverse recovery (RR) characteristics and on-state performance of 600V Silicon PiN diodes. The paper also discusses the influence of the measurement circuit on the reverse recovery of the high voltage diodes and it proposes a simple and effective mix-mode simulation tool for an accurate assessment of the diode performance in reverse recovery mode. © 2013 IEEE.

Characterizing the class of local metal sheet thickening processes

The need to create high-value products for specialist applications, and the search for efficient forming routes that obviate the need for some machining steps, is driving Interest In a novel class of forming processes aiming to create locally thickened features within sheet work- pieces. A number of novel forming processes have been proposed to meet this need, but it is as yet unclear which processes will be most effective in creating local thickening of various geometries, and many process configurations have yet to be tried. This paper aims to provide some basic principles for designing and characterising process behaviour. A simplified generic description of sheet thickening processes is provided, with two tools of variable operating on a sheet workpiece in plane strain, with different tool separations and motions parameterised. A comprehensive numerical study of the behaviour of this class of processes is conducted in Abaqus to predict the main characteristics of the material flow in each configuration. The results are used to classify the different basic behaviours that can be achieved by the sheet-bulk thickening processes and to give guidance on future process development, capability and applicability. © 2011 Wiley-VCH Verlag GmbH & Co. KGaA. Weinheim.

Local strain rate and curvature dependences of scalar dissipation rate transport in turbulent premixed flames: A direct numerical simulation analysis

The statistical behaviours of the instantaneous scalar dissipation rate Nc of reaction progress variable c in turbulent premixed flames have been analysed based on three-dimensional direct numerical simulation data of freely propagating statistically planar flame and V-flame configurations with different turbulent Reynolds number Ret. The statistical behaviours of N c and different terms of its transport equation for planar and V-flames are found to be qualitatively similar. The mean contribution of the density-variation term T1 is positive, whereas the molecular dissipation term (-D2) acts as a leading order sink. The mean contribution of the strain rate term T2 is predominantly negative for the cases considered here. The mean reaction rate contribution T3 is positive (negative) towards the unburned (burned) gas side of the flame, whereas the mean contribution of the diffusivity gradient term (D) assumes negative (positive) values towards the unburned (burned) gas side. The local statistical behaviours of Nc, T1, T2, T 3, (-D2), and f(D) have been analysed in terms of their marginal probability density functions (pdfs) and their joint pdfs with local tangential strain rate aT and curvature km. Detailed physical explanations have been provided for the observed behaviour. © 2014 Y. Gao et al.

An extension of slow feature analysis for nonlinear blind source separation

We present and test an extension of slow feature analysis as a novel approach to nonlinear blind source separation. The algorithm relies on temporal correlations and iteratively reconstructs a set of statistically independent sources from arbitrary nonlinear instantaneous mixtures. Simulations show that it is able to invert a complicated nonlinear mixture of two audio signals with a high reliability. The algorithm is based on a mathematical analysis of slow feature analysis for the case of input data that are generated from statistically independent sources. © 2014 Henning Sprekeler, Tiziano Zito and Laurenz Wiskott.

Detecting quantum entanglement by means of local operations and classical communication

Based on the positive maps separability criterion, we present a method for the detection of quantum entanglement of a shared bipartite quantum state, within the "distant labs" paradigm, using only local operations and classical communication.

Noiseless method for checking the Peres separability criterion by local operations and classical communication

We present a method for checking the Peres separability criterion in an arbitrary bipartite quantum state rho(AB) within local operations and classical communication scenario. The method does not require noise operation which is needed in making the partial transposition map physically implementable. The main task for the two observers, Alice and Bob, is to measure some specific functions of the partial transposed matrix. With these functions, they can determine the eigenvalues of rho(T)(AB)(B), among which the minimum serves as an entanglement witness.

Method for measuring two-qubit entanglement of formation by local operations and classical communication

We present a parametrically efficient method for measuring the entanglement of formation E-f in an arbitrarily given unknown two-qubit state rho(AB) by local operations and classical communication. The two observers, Alice and Bob, first perform some local operations on their composite systems separately, by which the desired global quantum states can be prepared. Then they estimate seven functions via two modified local quantum networks supplemented a classical communication. After obtaining these functions, Alice and Bob can determine the concurrence C and the entanglement of formation E-f.

A criterion for local interconvertibility between all-tripartite Gaussian states

We arrive at a necessary and sufficient criterion that can be readily used for interconvertibility between general, all-tripartite Gaussian states under local quantum operation. The derivation involves a systematic reduction that converts the original complex conditions in high-dimensional, 6n x 6n matrix space eventually into 2 x 2 matrix problems.

Local environment of Er3+ in Er-doped Si nanoclusters embedded in SiO2 films

The local environment of Er3+ in heavily Er-doped (Er, 2.5 at. %) Si nanoclusters embedded in SiO2 films annealed at various temperatures was investigated by using the fluorescence-extended x-ray absorption fine structure spectroscopy. The results show that annealing caused a large effect on the local environment of Er3+ surrounded by O atoms and the 1.54 mu m photoluminescence intensity. The correlation between the local environment around Er3+ and the corresponding 1.54 mu m photoluminescence was discussed. (c) 2006 American Institute of Physics.