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Auditory information processing studies applying signal detectability theory to auditory sensory responses
Conduct studies of auditory information processing emphasizing application of signal detectability theory to auditory sensory responses
Noise suppressor effect on signal detection and response speed and accuracy to sensory stimulations
Recently, quantitative models based on signal detection theory have been successfully applied to the prediction of human accuracy in visual search for a target that differs from distractors along a single attribute (feature search). The present paper extends these models for visual search accuracy to multidimensional search displays in which the target differs from the distractors along more than one feature dimension (conjunction, disjunction, and triple conjunction displays). The model assumes that each element in the display elicits a noisy representation for each of the relevant feature dimensions. The observer combines the representations across feature dimensions to obtain a single decision variable, and the stimulus with the maximum value determines the response. The model accurately predicts human experimental data on visual search accuracy in conjunctions and disjunctions of contrast and orientation. The model accounts for performance degradation without resorting to a limited-capacity spatially localized and temporally serial mechanism by which to bind information across feature dimensions.
A system is described which can aid in the search for radio signals from extraterrestrial sources, or in other applications characterized by low signal-to-noise ratios and very high data rates. The system follows a multichannel (16 million bin) spectrum analyzer, and has critical processing, system control, and memory fuctions. The design includes a moderately rich set of algorithms to be used in parallel to detect signals of unknown form. A multi-threshold approach is used to obtain high and low signal sensitivities. Relatively compact and transportable memory systems are specified.
Signal detection of auditory sensory responses to stimuli - auditory information processing
Research is described on potential improvements to the software used with the NASA 49.25 MHz wind profiler located at Kennedy Space Center. In particular, the analysis and results are provided of a study to (1) identify preferred mathematical techniques for the detection of atmospheric signals that provide wind velocities which are obscured by natural and man-made sources, and (2) to analyze one or more preferred techniques to demonstrate proof of the capability to improve the detection of wind velocities.
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Paired comparison tests of relative signals detected by capacitive and floating Langmuir probes in turbulent plasmas from 0.2 to 10MHz
Paired comparison tests of relative signal detected by capacitive and floating Langmuir probes in steady state turbulent plasma confined in magnetic mirror geometry
The Planet Detection Testbed is designed to simulate the architecture and operation of a space-borne four telescope nulling interferometer.
Cortical-evoked potentials were recorded from human subjects performing an auditory detection task with confidence rating responses. Unlike earlier studies that used similar procedures, the observation interval during which the auditory signal could occur was clearly marked by a visual cue light. By precisely defining the observation interval and, hence, synchronizing all perceptual decisions to the evoked potential averaging epoch, it was possible to demonstrate that high-confidence false alarms are accompanied by late-positive P3 components equivalent to those for equally confident hits. Moreover the hit and false alarm evoked potentials were found to covary similarly with variations in confidence rating and to have similar amplitude distributions over the scalp. In a second experiment, it was demonstrated that correct rejections can be associated with a P3 component larger than that for hits. Thus it was possible to show, within the signal detection paradigm, how the two major factors of decision confidence and expectancy are reflected in the P3 component of the cortical-evoked potential.
In the first part of this article, I describe a new approach to studying decision making in discrimination tasks that does not depend on the technical assumptions of signal detection theory (e.g., normality of the encoding distributions). Applying these new distribution-free tests to data from three experiments, I show that base rate and payoff manipulations had substantial effects on the participants' encoding distributions but no effect on their decision rules, which were uniformly unbiased in equal and unequal base rate conditions and in symmetric and asymmetric payoff conditions. In the second part of the article, I show that this seemingly paradoxical result is readily explained by the sequential sampling models of discrimination. I then propose a new, "model-free" test for response bias that seems to more properly identify both the nature and direction of the biases induced by the classical bias manipulations.
Currently, data quality is described in terms of spatial and temporal accuracy and precision [Holmqvist et al. in press]. While this approach provides precise errors in pixels, or visual angle, often experiments are more concerned with whether subjects'points of gaze can be said to be reliable with respect to experimentally-relevant areas of interest. This paper proposes a method to characterize oculometer data quality using Signal Detection Theory (SDT) [Marcum 1947]. SDT classification results in four cases: Hit (correct report of a signal), Miss (failure to report a ), False Alarm (a signal falsely reported), Correct Reject (absence of a signal correctly reported). A technique is proposed where subjects' are directed to look at points in and outside of an AOI, and the resulting Points of Gaze (POG) are classified as Hits (points known to be internal to an AOI are classified as such), Misses (AOI points are not indicated as such), False Alarms (points external to AOIs are indicated as in the AOI), or Correct Rejects (points external to the AOI are indicated as such). SDT metrics describe performance in terms of discriminability, sensitivity, and specificity. This paper presentation will provide the procedure for conducting this assessment and an example of data collected for AOIs in a simulated flightdeck environment.
A sudden excitation event of the Chandler wobble should induce the earth's rotation pole to undergo damped harmonic motion. This type of motion has been searched for in the observations of the Chandler wobble using techniques based upon the concept of a matched filter. Although the signal detection techniques used here were not sensitive enough to detect any such isolated sudden excitation events, the result that was obtained is consistent with a randomly excited model of the Chandler wobble.
Various methods for detecting narrow-band signals are evaluated. The characteristics of synchronized and unsynchronized pulses are examined. Synchronous, square law, regular pulse, and the general form detections are discussed. The CW, single pulse, synchronous, and four pulse detections are analyzed in terms of false alarm rate and threshold relative to average noise power. Techniques for saving memory and retaining sensitivity are described. Consideration is given to nondrifting CW detection, asynchronous pulse detection, interpolative and extrapolative pulse detectors, and finite and infinite pulses.
We demonstrated upconversion assisted detection of a 2.05-micron signal by sum frequency generation to generate a 700-nm light using a bulk periodically poled lithium niobate crystal. The achieved 94% intrinsic upconversion efficiency and 22.58% overall detection efficiency at a pW level of 2.05 micron pave the path to detect extremely weak infrared (IR) signals for remote sensing applications.
An investigation to develop, implement, and evaluate signal analysis techniques for the detection and classification of incipient mechanical failures in turbomachinery is reviewed. A brief description of the Space Shuttle Main Engine (SSME) test/measurement program is presented. Signal analysis techniques available to describe dynamic measurement characteristics are reviewed. Time domain and spectral methods are described, and statistical classification in terms of moments is discussed. Several of these waveform analysis techniques have been implemented on a computer and applied to dynamc signals. A laboratory evaluation of the methods with respect to signal detection capability is described. A unique coherence function (the hyper-coherence) was developed through the course of this investigation, which appears promising as a diagnostic tool. This technique and several other non-linear methods of signal analysis are presented and illustrated by application. Software for application of these techniques has been installed on the signal processing system at the NASA/MSFC Systems Dynamics Laboratory.