To bin or not to bin? Deselecting print back-runs available electronically at Imperial College London Library

Accepted versio

Attributes of GRB Pulses: Bayesian Blocks Analysis of TTE Data; a Microburst in GRB 920229

Bayesian Blocks is a new time series algorithm for detecting localized structures (spikes or shots), revealing pulse shapes, and generally characterizing intensity variations. It maps raw counting data into a maximum likelihood piecewise constant representation of the underlying signal. This bin-free method imposes no lower limit on measurable time scales. Applied to BATSE TTE data, it reveals the shortest know burst structure -- a spike superimposed on the main burst in GRB 920229 = Trigger 1453, with rise and decay timescales ~ few 100 microseconds.Comment: 5 pages, 2 figures; presented at the 4th Huntsville Gamma-ray Burst Symposiu

Experimental performance of a conical pressure probe at Mach numbers of 3.0, 4.5, and 6.0

Wind tunnel investigation of performance of conical pressure probe at hypersonic speed

The irrelevant sound effect: What needs modelling and a tentative model

Original article can be found at: http://www.informaworld.com/smpp/title~content=t713683590 Copyright Informa / Taylor and Francis GroupThis paper reviews the literature on the irrelevant sound effect and concludes that, contrary to some claims, the data consistently show that irrelevant sound and articulatory suppression are not functionally equivalent. We evaluate the contribution of Larsen and Baddeley (in press) and briefly discuss additional data in support of their position. We perform an error analysis on data from their third experiment and simulate detailed aspects of those data using our primacy model of immediate serial recall. Our model is briefly related to a number of fndings in the literature on irrelevant sound.Peer reviewe

Coping with speaker-related variation via abstract phonemic categories

Listeners can cope with considerable variation in the way that different speakers talk. We argue here that they can do so because of a process of phonological abstraction in the speech-recognition system. We review evidence that listeners adjust the bounds of phonemic categories after only very limited exposure to a deviant realisation of a given phoneme. This learning can be talker-specific and is stable over time; further, the learning generalizes to previously unheard words containing the deviant phoneme. Together these results suggest that the learning involves adjustment of prelexical phonemic representations which mediate between the speech signal and the mental lexicon during word recognition. We argue that such an abstraction process is inconsistent with claims made by some recent models of language processing that the mental lexicon consists solely of multiple detailed traces of acoustic episodes. Simulations with a purely episodic model without functional prelexical abstraction confirm that such a model cannot account for the evidence on lexical generalization of perceptual learning. We conclude that abstract phonemic categories form a necessary part of lexical access, and that the ability to store talker-specific knowledge about those categories provides listeners with the means to deal with cross-talker variation