Human visual signal detection by simultaneous observation through multiple channels: Experimental study of decision behavior

摘要

Performance of six subjects (Ss) in detecting randomly occurring visual signals of filtered sine bursts recorded on paper through four similar noisy channels is investigated and their decision behavior in that task is modelled. The noise channels were additive white Gaussian and independent from each other. This study confirms previous results that the detection outcome from a single channel may be predicted from the maximum signal-to-noise ratio at the output of a filter matched to signal and also that Ss make fewer errors than the optimum matched filter detector. The pattern of improvement in detection in the case of multiple channels was found to be similar to a combination of analog-digital aggregation scheme. Observations on Ss' decision behavior in these experiments were incorporated into a pattern recognition algorithm for single channel detection and into an information processing model for multiple channel aggregation.