scispace - formally typeset
Search or ask a question
Institution

Raytheon

CompanyWaltham, Massachusetts, United States
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.
Topics: Signal, Antenna (radio), Radar, Turbine, Amplifier


Papers
More filters
Patent
Khiem V. Cai1, Allan L. Levine1
05 Dec 1996
TL;DR: In this article, a digital signal processor is provided which is compatible with a large variety of modulation processes (e.g., BPSK, QPSK and PSK), and is particularly suited for realization as an application-specific integrated circuit (ASIC) which can be integrated in multiband, multimode transceivers.
Abstract: A digital signal processor is provided which is compatible with a large variety of modulation processes (e.g., BPSK, QPSK,π/4 QPSK, M-ary FSK and M-ary PSK). The processor has a transmit section which can convert input data streams into baseband I and Q signals and a receive section which can recover data streams from input baseband I and Q signals. The transmit section includes a direct I/Q modulator and a common phase modulator and the receive section includes an M-FSK to M-PSK converter and a common phase demodulator. The processor is particularly suited for realization as an application-specific integrated circuit (ASIC) which can be integrated in multiband, multimode transceivers.

69 citations

Journal ArticleDOI
TL;DR: It is shown in one dimension that for equiprobable component distributions of almost any functional form and differing only by translation the authors can obtain category distribution estimators which converge uniformly over the real line with probability 1.
Abstract: Adaptive signal detection and pattern recognition can be viewed as a problem in statistical classification wherein the partitioning of an n-dimensional sample space into category (signal) regions is determined through estimation from a set of samples from the categories When the correct associations of the samples are known, the problem is the commonly treated supervised one This paper, examining the nonsupervised case wherein the correct associations of the samples are unknown, demonstrates that it is possible under extremely general conditions to achieve effective adaptation without supervision With particular emphasis on a two-category (binary detection) model, general conditions are described under which nonsupervised adaptation is possible, and specific simple yet rapidly convergent techniques are presented under varying degrees of prior knowledge of the statistical properties of the data Most of the paper is concerned with a two-category case where the corresponding (equiprobable) distributions differ only in location The paper proceeds by examining the over-all probability distribution comprised of the two component category distributions, and the adaptation treated is directed toward determining the decision boundary, or the distribution parameters necessary for defining it For univariate normal distributions various estimators (and their convergence properties) of the over-all mean are examined For multivariate monotone (including normal) distributions the over-all sample covariance matrix is used to obtain the component covariance matrices when these are general (including the colored noise case), or simply to obtain the principal eigenvector (of the overall matrix) when the component distributions are spherically symmetric (white noise) A hill-climbing algorithm is included These results for the important model of binary signal detection in gaussian noise demonstrate that no prior knowledge of the signal or noise parameters is required for nonsupervised adaptation to the optimum detector It is shown in one dimension that for equiprobable component distributions of almost any functional form and differing only by translation we can obtain category distribution estimators which converge uniformly over the real line with probability 1 Considered also are the case of different a priori probabilities, the problem of tracking, and some aspects of the multiple-category problem

69 citations

Patent
James C. Ianni1
26 Aug 2008
TL;DR: In this article, a first list of all files stored on all nodes of the cluster, compiling a second list indicative of unique files and the number of unique nodes on which each unique file is stored from the first list, determining, from the second list, unique files which are not stored at all nodes, which files are required by all nodes and which files must be added to each node.
Abstract: In accordance with a particular embodiment of the present disclosure, common cluster files residing on nodes in a cluster may be managed by compiling a first list of all files stored on all nodes of the cluster, compiling a second list indicative of unique files and the number of nodes on which each unique file is stored from the first list, determining, from the second list, unique files which are not stored on all nodes, determining, from the second list, which files are required by all nodes, and determining, from the first list and the second list, which files must be added to each node.

69 citations

Proceedings ArticleDOI
25 Jun 2005
TL;DR: A Genetic Programming approach to evolve cooperative controllers for teams of UAVs is presented, which is robust to changes in initial mission parameters and approach the optimal bound for time-to-completion.
Abstract: We present a Genetic Programming approach to evolve cooperative controllers for teams of UAVs. Our focus is a collaborative search mission in an uncertain and/or hostile environment. The controllers are decision trees constructed from a set of low-level functions. Evolved decision trees are robust to changes in initial mission parameters and approach the optimal bound for time-to-completion. We compare results between steady-state and generational approaches, and examine the effects of two common selection operators.

69 citations

Patent
20 Jul 1995
TL;DR: In this paper, a deterministic network protocol for connecting critical sensors, actuators and computing elements on a bi-directional, time-multiplexed, fiber optic or other media data bus, such that critical messages have concisely bounded latency and non-critical messages may be sent without impacting critical messages.
Abstract: A deterministic network protocol for connecting critical sensors, actuators and computing elements on a bi-directional, time-multiplexed, fiber optic or other media data bus, such that critical messages have concisely bounded latency and non-critical messages may be sent without impacting critical messages. It is a unique combination of a time-slot allocation protocol and a contention-based protocol in which global synchronization information is passed on the data media via a synchronization beacon.

69 citations


Authors

Showing all 15293 results

NameH-indexPapersCitations
Peter J. Kahrilas10958646064
Edward J. Wollack104732102070
Duong Nguyen9867447332
Miroslav Krstic9595542886
Steven L. Suib8986234189
Gabriel M. Rebeiz8780632443
Charles W. Engelbracht8321028137
Paul A. Grayburn7739726880
Eric J. Huang7220122172
Thomas F. Eck7215032965
David M. Margolis7022717314
David W. T. Griffith6528814232
Gerhard Klimeck6568518447
Nickolay A. Krotkov6321911250
Olaf Stüve6329014268
Network Information
Related Institutions (5)
United States Naval Research Laboratory
45.4K papers, 1.5M citations

86% related

Bell Labs
59.8K papers, 3.1M citations

83% related

Samsung
163.6K papers, 2M citations

83% related

Georgia Institute of Technology
119K papers, 4.6M citations

83% related

Hewlett-Packard
59.8K papers, 1.4M citations

82% related

Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
20232
20228
2021265
2020655
2019579
2018457