2,392,194 research outputs found

    Signal processing at the Poker Flat MST radar

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    Signal processing for Mesosphere-Stratosphere-Troposphere (MST) radar is carried out by a combination of hardware in high-speed, special-purpose devices and software in a general-purpose, minicomputer/array processor. A block diagram of the signal processing system is presented, and the steps in the processing pathway are described. The current processing capabilities are given, and a system offering greater coherent integration speed is advanced which hinges upon a high speed preprocessor

    Technology Policy, Gender, and Cyberspace

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    Event based sampling occurs when the time instants are measured everytime the amplitude passes certain pre-defined levels. This is in contrast with classical signal processing where the amplitude is measured at regular time intervals. The signal processing problem is to separate the signal component from noise in both amplitude and time domains. Event based sampling occurs in a variety of applications. The purpose here is to explain the new types of signal processing problems that occur, and identify the need for processing in both the time and event domains. We focus on rotating axles, where amplitude disturbances are caused by vibrations and time disturbances from measurement equipment. As one application, we examine tire pressure monitoring in cars where suppression of time disturbance is of utmost importance

    GPGPU for track finding in High Energy Physics

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    The LHC experiments are designed to detect large amount of physics events produced with a very high rate. Considering the future upgrades, the data acquisition rate will become even higher and new computing paradigms must be adopted for fast data-processing: General Purpose Graphics Processing Units (GPGPU) is a novel approach based on massive parallel computing. The intense computation power provided by Graphics Processing Units (GPU) is expected to reduce the computation time and to speed-up the low-latency applications used for fast decision taking. In particular, this approach could be hence used for high-level triggering in very complex environments, like the typical inner tracking systems of the multi-purpose experiments at LHC, where a large number of charged particle tracks will be produced with the luminosity upgrade. In this article we discuss a track pattern recognition algorithm based on the Hough Transform, where a parallel approach is expected to reduce dramatically the execution time.Comment: 6 pages, 4 figures, proceedings prepared for GPU-HEP 2014 conference, submitted to DESY-PROC-201

    THE GERMANIUM EXTRACTION FROM TECHNOGENIC RAW MATERIALS BY MICROBIOLOGICAL METHODS

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    The results have practical significance and can be the basis for developing a unified biotechnological method of technogenic waste processing with a purpose of their sterilization and detoxification with simultaneous obtaining concentrates of valuable metals

    On the Analysis of Neural Networks for Image Processing

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    This paper illustrates a novel method to analyze artificial neural networks so as to gain insight into their internal functionality. To this purpose, we will show analysis results of some feed-forward¿error-back-propagation neural networks for image processing. We will describe them in terms of domain-dependent basic functions, which are, in the case of the digital image processing domain, differential operators of various orders and with various angles of operation. Some other pixel classification techniques are analyzed in the same way, enabling easy comparison
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