We consider a general linear filtering operation on an autoregressive moving average (ARMA) time series. The variance of the filter output, which is an important quantity in many applications, is not known with certainty because it depends on the true ARMA parameters. We derive an expression for the sensitivity (i.e., the partial derivative) of the output variance with respect to deviations in ...

Various papers have analyzed the noisy optimization of convex functions. This analysis has been made according to several criteria used to evaluate the performance of algorithms: uniform rate, simple regret and cumulative regret. We propose an iterative optimization framework, a particular instance of which, using Hessian approximations, provably (i) reaches the same rate as Kiefer-Wolfowitz al...

Independent Component Analysis (ICA) designed for complete bases is used in a variety of applications with great success, despite the often questionable assumption of having N sensors and M sources with NQM. In this article, we assume a source model with more sources than sensors (M>N), only L<N of which are assumed to have a non-Gaussian distribution. We argue that this is a realistic source m...

A 49-d feeding trial, using 192 growingfinishing pigs (avg initial wt, 32 kg), was conducted to identify pigs of widely differing average daily gains (ADG) when fed 16% crude protein diets containing either 0, 7.5 or 15% corn cobs. There were linear decreases in both ADG (P<.01) and gain/feed (P<.001) with increasing levels of dietary corn cobs. Average daily feed intake increased linearly (P<....

This study was conducted to investigate the effects of increasing levels of extracts of Byrsonima crassifolia, Celtis pallida, Enterolobium cyclocarpum, Fraxinus excelsior, Ficus trigonata, Phoradendrom brevifolium and Prunus domestica on in vitro gas production (GP) and ruminal fermentation of a high concentrate diet. Plant extracts were prepared at 1 g dry matter (DM)/8 mL of solvent mixture ...

This paper aims at presenting our algorithm used to make submission for the NIST 2013-2014 speaker recognition ivector challenge. The fixed dimensional i-vector representation of speech utterances has attracted attentions from other communities. This challenge focuses on the task of speaker detection using i-vectors derived from conversational telephony speech data. However, the unlabeled i-vec...

We present a tumor localization method for diffuse optical tomography using linearly constrained minimum variance (LCMV) beamforming. Beamforming is a spatial filtering technique where signals from certain directions can be enhanced while noise and interference from other directions are suppressed. In our method, we tessellate the domain into small voxels and regard each voxel as a possible pos...

Antenna arrays that receive emissions from spatially spread sources require beamformers with wider beamwidths than point source beamformers. The framework of linearly constrained minimum variance beamforming with quadratic pattern constraints (LCMV-QPC) is used to develop beamformers with a specified main beamwidth and sidelobe levels. The problem is formulated by imposing a set of inequality c...

In this paper an inverse QR decomposition based recursive least-squares algorithm for linearly constrained minimum variance filtering is proposed. The proposed algorithm is numerically stable in finite precision environments and is suitable for implementation in systolic arrays or DSP vector architectures. Its performance is illustrated by simulations of a blind receiver for a multicarrier CDMA...

Speech acquired from an array of distant microphones is affected by ambient noise and reverberation. Single channel linearly constrained minimum variance (LCMV) filters have been proposed to remove ambient noise. In this paper, an algorithm for joint noise cancellation and dereverberation using a multi channel LCMV filter in the frequency domain is proposed. A single channel LCMV filter which a...