11 research outputs found

    Interaural Correlation Fails to Account for Detection in a Classic Binaural Task: Dynamic ITDs Dominate N0Sπ Detection

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    Binaural signal detection in an NoSπ task relies on interaural disparities introduced by adding an antiphasic signal to diotic noise. What metric of interaural disparity best predicts performance? Some models use interaural correlation; others differentiate between dynamic interaural time differences (ITDs) and interaural level differences (ILDs) of the effective stimulus. To examine the relative contributions of ITDs and ILDs in binaural detection, we developed a novel signal processing technique that selectively degrades different aspects (potential cues) of binaural stimuli (e.g., only ITDs are scrambled). Degrading a particular cue will affect performance only if that cue is relevant to the binaural processing underlying detection. This selective scrambling technique was applied to the stimuli of a classic N0Sπ task in which the listener had to detect an antiphasic 500-Hz signal in the presence of a diotic wideband noise masker. Data obtained from five listeners showed that (1) selective scrambling of ILDs had little effect on binaural detection, (2) selective scrambling of ITDs significantly degraded detection, and (3) combined scrambling of ILDs and ITDs had the same effect as exclusive scrambling of ITDs. Regarding the question which stimulus properties determine detection, we conclude that for this binaural task (1) dynamic ITDs dominate detection performance, (2) ILDs are largely irrelevant, and (3) interaural correlation of the stimulus is a poor predictor of detection. Two simple stimulus-based models that each reproduce all binaural aspects of the data quite well are described: (1) a single-parameter detection model using ITD variance as detection criterion and (2) a compressive transformation followed by a crosscorrelation analysis. The success of both of these contrasting models shows that our data alone cannot reveal the mechanisms underlying the dominance of ITD cues. The physiological implications of our findings are discussed

    Ku-band interferometry

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    Construction of Ku band radio interferometer and preliminary observation

    Ku-band interferometry.

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    Also issued as a Ph.D. thesis in the Dept. of Electrical Engineering, 1970.Bibliography: p.107

    Adaptive systems in digital communication designs

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    Thesis (M.S.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 1996.Includes bibliographical references (leaves 98-100).by Xinben Garrison Qian.M.S

    Space programs summary no. 37-48, volume 2, for the period September 1 to October 31, 1967. The deep space network

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    Navigation technology, communication equipment, antenna engineering, and ground station operations for Deep Space Network /DSN

    Spectral analysis methods for noisy sampled-data systems

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    The 1992 4th NASA SERC Symposium on VLSI Design

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    Papers from the fourth annual NASA Symposium on VLSI Design, co-sponsored by the IEEE, are presented. Each year this symposium is organized by the NASA Space Engineering Research Center (SERC) at the University of Idaho and is held in conjunction with a quarterly meeting of the NASA Data System Technology Working Group (DSTWG). One task of the DSTWG is to develop new electronic technologies that will meet next generation electronic data system needs. The symposium provides insights into developments in VLSI and digital systems which can be used to increase data systems performance. The NASA SERC is proud to offer, at its fourth symposium on VLSI design, presentations by an outstanding set of individuals from national laboratories, the electronics industry, and universities. These speakers share insights into next generation advances that will serve as a basis for future VLSI design

    The deep space network

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    Progress is reported in flight project support, tracking and data acquisition, research technology, network engineering, hardware and software implementation, and operations

    The estimation and compensation of processes with time delays

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    The estimation and compensation of processes with time delays have been of interest to academics and practitioners for several decades. A full review of the literature for both model parameter and time delay estimation is presented. Gradient methods of parameter estimation, in open loop, in the time and frequency domains are subsequently considered in detail. Firstly, an algorithm is developed, using an appropriate gradient algorithm, for the estimation of all the parameters of an appropriate process model with time delay, in open loop, in the time domain. The convergence of the model parameters to the process parameters is considered analytically and in simulation. The estimation of the process parameters in the frequency domain is also addressed, with analytical procedures being defined to provide initial estimates of the model parameters, and a gradient algorithm being used to refine these estimates to attain the global minimum of the cost function that is optimised. The focus of the thesis is subsequently broadened with the consideration of compensation methods for processes with time delays. These methods are reviewed in a comprehensive manner, and the design of a modified Smith predictor, which facilitates a better regulator response than does the Smith predictor, is considered in detail. Gradient algorithms are subsequently developed for the estimation of process parameters (including time delay) in closed loop, in the Smith predictor and modified Smith predictor structures, in the time domain; the convergence of the model parameters to the process parameters is considered analytically and in simulation. The thesis concludes with an overview of the methods developed, and projections regarding future developments in the topics under consideration
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