Nonparametric forecasting in time series: a comparative study

The problem of predicting a future value of a time series is considered in this paper. If the series follows a stationary Markov process, this can be done by nonparametric estimation of the autoregression function. Two forecasting algorithms are introduced. They only differ in the nonparametric kernel-type estimator used: the Nadaraya-Watson estimator and the local linear estimator. There are three major issues in the implementation of these algorithms: selection of the autoregressor variables; smoothing parameter selection and computing prediction intervals. These have been tackled using recent techniques borrowed from the nonparametric regression estimation literature under dependence. The performance of these nonparametric algorithms has been studied by applying them to a collection of 43 well-known time series. Their results have been compared to those obtained using classical Box-Jenkins methods. Finally, the practical behaviour of the methods is also illustrated by a detailed analysis of two data sets.Galicia. Consellería de Innovación, Industria e Comercio; PGIDT01PXI10505PRGalicia. Consellería de Innovación, Industria e Comercio; PGIDT03PXIC10505PNMinisterio de Ciencia y Tecnología; BMF2002-0026

The Zero Resource Speech Challenge 2017

We describe a new challenge aimed at discovering subword and word units from raw speech. This challenge is the followup to the Zero Resource Speech Challenge 2015. It aims at constructing systems that generalize across languages and adapt to new speakers. The design features and evaluation metrics of the challenge are presented and the results of seventeen models are discussed.Comment: IEEE ASRU (Automatic Speech Recognition and Understanding) 2017. Okinawa, Japa

Spatial Interference: From Coherent To Incoherent

It is well known that direct observation of interference and diffraction pattern in the intensity distribution requires a spatially coherent source. Optical waves emitted from portions beyond the coherence area possess statistically independent phases, and will degrade the interference pattern. In this paper we show an optical interference experiment, which seems contrary to our common knowledge, that the formation of the interference pattern is related to a spatially incoherent light source. Our experimental scheme is very similar to Gabor's original proposal of holography[1], just with an incoherent source replacing the coherent one. In the statistical ensemble of the incoherent source, each sample field produces a sample interference pattern between object wave and reference wave. These patterns completely differ from each other due to the fluctuation of the source field distribution. Surprisingly, the sum of a great number of sample patterns exhibits explicitly an interference pattern, which contains all the information of the object and is equivalent to a hologram in the coherent light case. In this sense our approach would be valuable in holography and other interference techniques for the case where coherent source is unavailable, such as x-ray and electron sources.Comment: 8 pages, 5 figure