Raytheon

About: Raytheon is a company organization based out in Waltham, Massachusetts, United States. It is known for research contribution in the topics: Signal & Antenna (radio). The organization has 15290 authors who have published 18973 publications receiving 300052 citations.

The history of the development of the rectenna

Abstract: The history of the development of the rectenna is reviewed through its early conceptual developmental phases. Some selective aspects of the current solar power satellite rectenna development are examined.

A Comprehensive System for Computer-Aided Tolerance Analysis of 2-D and 3-D Mechanical Assemblies

Abstract: Tolerance analysis of assemblies promotes concurrent engineering by bringing engineering requirements and manufacturing capabilities together in a common model. By further integrating the engineering modeling and analysis with a CAD system, a practical tool for product and process development is created. It provides a quantitative design tool for predicting the effects of manufacturing variation on performance and cost in a computer-based design environment.

Segmented thermally insulating coating

Abstract: A gas turbine article includes a substrate, a plurality of geometric surface features that protrude from the substrate, and a thermally insulating topcoat disposed over the plurality of geometric surface features. The thermally insulating topcoat includes segmented portions that are separated by faults that extend through the topcoat from the geometric surface features.

Domain adaptation via within-class covariance correction in I-vector based speaker recognition systems

Abstract: In this paper we propose a technique of Within-Class Covariance Correction (WCC) for Linear Discriminant Analysis (LDA) in Speaker Recognition to perform an unsupervised adaptation of LDA to an unseen data domain, and/or to compensate for speaker population difference among different portions of LDA training dataset. The paper follows on the study of source-normalization and inter-database variability compensation techniques which deal with multimodal distribution of i-vectors. On the DARPA RATS (Robust Automatic Transcription of Speech) task, we show that, with two hours of unsupervised data, we improve the Equal-Error Rate (EER) by 17.5%, and 36% relative on the unmatched and semi-matched conditions, respectively. On the Domain Adaptation Challenge we show up to 70% relative EER reduction and we propose a data clustering procedure to identify the directions of the domain-based variability in the adaptation data.