In this article we develop an extension to the signal detection theory framework to separately estimate internal noise arising from representational and decision processes. Our approach constrains signal detection theory models with decision noise by combining a multipass external noise paradigm with confidence rating responses. In a simulation study we present evidence that representation and ...

The detection performance of the generalized detector (GD) constructed based on the generalized approach to signal processing in noise is evaluated under homogeneous and non-homogeneous noise. The GD adaptive threshold is derived and defined applying an appropriate noise power estimation using the sliding window technique. The direct close expressions for the GD average probability of detection...

Contrast detection is impaired in amblyopes. To understand the contrast processing deficit in amblyopia, we studied the effects of masking noise on contrast threshold in amblyopic macaque monkeys. Amblyopia developed as a result of either experimentally induced strabismus or anisometropia. We used random spatiotemporal broadband noise of varying contrast power to mask the detection of sinusoida...

A signal detection system using noise statistical processing is proposed. By approaching the problems of low voltage and high noise from miniaturization of a device from a stochastic point of view, a faint-signal receiving system that can effectively detect subthreshold and noise level signals has been developed. In addition, an alternative to statistical processing is proposed, and would be su...

Automatic speech recognition performance tends to be degraded in noisy conditions. Spectral subtraction is a simple, popular approach of noise compensation. In conventional spectral subtraction [1, 2], noise statistics are updated during speech gaps and subtracted from a corrupt signal during speech intervals. Some means of explicit speech, non-speech detection is therefore essential. Recent pr...

Remote sensing data sets frequently suffer from noise due to atmospheric conditions and instrument issues. This noise negatively affects the usability of these data sets and therefore noise reduction techniques are frequently used to reduce the impact of noise. A well-known remote sensing data set, MODIS Enhance Vegetation Index (EVI), measures the amount of vegetation (based on surface reflect...

Detection of intensity flashes in the blowfly photoreceptor is limited by photon noise in the input signal as well as noise contributed by transduction components within the photoreceptor. Our analysis uses an ideal observer and a model of blowfly phototransduction to compute the threshold for optimal detection of intensity flashes as background intensity varies. We find that detection threshol...

The problem of HOS-based signal detection methods applied in real communication systems is addressed. The Locally Optimum (LO) criterion is selected from a large number of detection criteria. It can be applied either under the ideal (but often not realistic) assumption of Gaussian background noise, or on the basis of realistic statistical models of channel noise. Conventional Fourier analysis (...

avoid interference from secondary users to primary holders with license in spectrum, it is need to have an appropriate spectrum sensing. In methods like spectrum sensing, where samples of noise are correlated, the impairments from independent noise samples do not provide optimum performances. So, in case of random signals over a weakly correlated noise model in fading channels requires a locall...