Now showing items 1-6 of 6
Robust methods tailored for non-Gaussian narrowband array processing
Array processing algorithms generally assume that the received signal, composed of both narrowband signals and noise, is Gaussian, which is not true in general. In the context of the narrowband array processing problem, ...
Optimal binaural processing based on point process models of preprocessed cues
In localizing high-frequency tonal signals in the horizontal plane, the lateral superior olive (LSO) encodes the interaural level differences (ILD), the crucial cue for azimuthal angle extraction at some nuclei more central ...
Change detection using types for non-stationary processes
Space shuttle operation requires the monitoring of a large number of stationary signals in the search for "anomalies." This problem amounts to determining whether a change has occurred in a signal having a partially known ...
On models of signal processing by neuronal patterns
A theory of information flow through sensory nervous systems is formulated as the representation of a finite number of events by a set of parallel point process channels with limited signaling sets. As a balance among ...
A geometry for detection theory
The optimal detector for a binary detection problem under a variety of criteria is the likelihood ratio test. Despite this simple characterization of the detector, analytic performance analysis in most cases is difficult ...
Analysis of long-range dependence in auditory-nerve fiber recordings
The pattern of occurrence of isolated action potentials recorded from the cat's auditory nerve fiber is modeled over short time scales as a renewal process. For counting times greater than one second, the count variance-to-mean ...