Literatura académica sobre el tema "Decorrelation noise"

Desynchronizing responses to correlated noise: a mechanism for binaural masking level differences at the inferior colliculus. We examined the adequacy of decorrelation of the responses to dichotic noise as an explanation for the binaural masking level difference (BMLD). The responses of 48 low-frequency neurons in the inferior colliculus of anesthetized guinea pigs were recorded to binaurally presented noise with various degrees of interaural correlation and to interaurally correlated noise in the presence of 500-Hz tones in either zero or π interaural phase. In response to fully correlated noise, neurons’ responses were modulated with interaural delay, showing quasiperiodic noise delay functions (NDFs) with a central peak and side peaks, separated by intervals roughly equivalent to the period of the neuron’s best frequency. For noise with zero interaural correlation (independent noises presented to each ear), neurons were insensitive to the interaural delay. Their NDFs were unmodulated, with the majority showing a level of activity approximately equal to the mean of the peaks and troughs of the NDF obtained with fully correlated noise. Partial decorrelation of the noise resulted in NDFs that were, in general, intermediate between the fully correlated and fully decorrelated noise. Presenting 500-Hz tones simultaneously with fully correlated noise also had the effect of demodulating the NDFs. In the case of tones with zero interaural phase, this demodulation appeared to be a saturation process, raising the discharge at all noise delays to that at the largest peak in the NDF. In the majority of neurons, presenting the tones in π phase had a similar effect on the NDFs to decorrelating the noise; the response was demodulated toward the mean of the peaks and troughs of the NDF. Thus the effect of added tones on the responses of delay-sensitive inferior colliculus neurons to noise could be accounted for by a desynchronizing effect. This result is entirely consistent with cross-correlation models of the BMLD. However, in some neurons, the effects of an added tone on the NDF appeared more extreme than the effect of decorrelating the noise, suggesting the possibility of additional inhibitory influences.

In this paper, two different receiver structures to multiuser detection that are appropriate for the code-division multiple-access systems with antenna arrays in fading channels are investigated and compared. We analyze and compare the performance of the two different multiuser detection structures for uplink or downlink channels. The number of elements of receiving antenna array may be limited in the downlink channel due to the small size of receivers. We assume a synchronous system, but it can be easily extended to an asynchronous system. The first approach is based on the distributed decorrelator where the signal decorrelation is performed by each receiving antenna element independently and decorrelated outputs are combined according to the maximum ratio. The second approach is the central decorrelator where the signal decorrelation is performed once collectively on the outputs from all elements of receiving antenna array. Both decorrelators provide the same performance in the additive white Gaussian noise channels. The distributed decorrelator provides the better performance in flat fading channels. We employ the decorrelator to demonstrate our results. The results discussed in the present paper can be extended to other configurations such as the blind adaptive space-time multiuser detection.

In underwater radiated noise measurement using a vertical linear array, a diagonalization-decorrelation-based diagonal denoising method is proposed to improve the denoising effect for spatially correlated noise. Firstly, the ambient noise cross-spectral matrix is measured without the radiated noise source. Subsequently, the eigenvector matrix of the ambient noise cross-spectral matrix is utilized to implement a unitary transformation for the received data, which eliminates the correlation of the received noise and transforms the received noise cross-spectral matrix into a diagonal matrix, then the noise components are removed by diagonal denoising. Finally, the denoised cross-spectral matrix is used to estimate the power of the radiated noise by beamforming. Consequently, the influence of spatially correlated noise on radiated noise measurement is reduced. The effectiveness of the proposed method is validated and compared with the diagonal denoising method and the whitening-decorrelation-based diagonal denoising method via numerical simulations and experimental data. Under the ideal condition, the noise reduction performances of the proposed method and the whitening-decorrelation-based diagonal denoising method are equal and better than that of the diagonal denoising method. In practice, the number of snapshots is limited, so there is an inevitable mismatch between the ambient noise cross-spectral matrix and the received noise cross-spectral matrix due to the randomness of noise. The mismatch results in imperfect whitening and diagonalization, which reduces the denoising effect. However, the simulation results indicate that the proposed method still reduces more correlated noise and has a better performance on underwater radiated noise measurement compared with the diagonal denoising method and the whitening-decorrelation-based diagonal denoising method even if the number of snapshots is finite.

In this work, we extended a procedure for the spatial decorrelation of fully-developed speckle, originally developed for single-polarization SAR data, to fully-polarimetric SAR data. The spatial correlation of the noise depends on the tapering window in the Fourier domain used by the SAR processor to avoid defocusing of targets caused by Gibbs effects. Since each polarimetric channel is focused independently of the others, the noise-whitening procedure can be performed applying the decorrelation stage to each channel separately. Equivalently, the noise-whitening stage is applied to each element of the scattering matrix before any multilooking operation, either coherent or not, is performed. In order to evaluate the impact of a spatial decorrelation of the noise on the performance of polarimetric despeckling filters, we make use of simulated PolSAR data, having user-defined polarimetric features. We optionally introduce a spatial correlation of the noise in the simulated complex data by means of a 2D separable Hamming window in the Fourier domain. Then, we remove such a correlation by using the whitening procedure and compare the accuracy of both despeckling and polarimetric features estimation for the three following cases: uncorrelated, correlated, and decorrelated images. Simulation results showed a steady improvement of performance scores, most notably the equivalent number of looks (ENL), which increased after decorrelation and closely attained the value of the uncorrelated case. Besides ENL, the benefits of the noise decorrelation hold also for polarimetric features, whose estimation accuracy is diminished by the correlation. Also, the trends of simulations were confirmed by qualitative results of experiments carried out on a true Radarsat-2 image.

As a by-product of Interferometric Synthetic Aperture Radar (SAR, InSAR) technique, interferometric coherence is a measure of the decorrelation noise for InSAR observation, where the lower the coherence value, the more serious the decorrelation noise. In the densely vegetated area, the coherence value could be too low to obtain any valuable signals, leading to the degradation of InSAR performance and the possible waste of expensive SAR data. Normalized Difference Vegetation Index (NDVI) value is a measure of the vegetation coverage and can be estimated from the freely available optical satellite images. In this paper, a multi-stage model is established to quantitatively estimate the decorrelation noise for vegetable areas based on Landsat-derived NDVI prior to the acquisition of SAR data. The modeling process is being investigated with the L-band ALOS-1/PALSAR-1 data and the Landsat-5 optical data acquired in the Meitanba area of Hunan Province, China. Furthermore, the reliability of the established model is verified in the Longhui area, which is situated near the Meitanba area. The results demonstrate that the established model can quantitatively estimate InSAR decorrelation associated with the vegetation coverage.

Noise reduction is one of the most important processes to enhance the quality of images. This paper proposes a statistical filter, the decorrelation stretch filter for the reduction of Poisson noise that occurs frequently in galaxy images. The primary purpose of decorrelation stretch is visual enhancement. Decorrstretch is applied to the three band images but can also work on arbitrary number of bands. This filter enhances the color separation of an image with significant band-band correlation. Effectiveness of the proposed filter is compared on the basis of Peak Signal to Noise Ratio (PSNR), Mean Square Error (MSE).

The presence of control signal feedback to the reference microphone in feedforward active control systems deteriorates the control performance. A four-stage method is proposed in this paper to carry out online feedback path modelling with the control signal. It consists of controller initialization, feedback path modelling using decorrelation filters, active control operation, and feedback path change detection for maintaining the control operation. In contrast to the existing auxiliary noise injection method, the proposed method uses five switches and three thresholds to control and maintain the system stability by avoiding the interference between control operation and feedback path modelling, and adaptive decorrelation filters are used to increase the feedback path modelling performance. Simulation results reveal that the proposed method is capable of tracking feedback path changes without injecting any auxiliary noise and maintaining the noise reduction performance and stability of the system.

To estimate the motion state of object feature point in image space, an adaptive decorrelation Kalman filtering model is proposed in this paper. The model is based on the Kalman filtering method. A first-order Markov sequence model is used to describe the colored measurement noise. To eliminate the colored noise, the measurement equation is reconstructed and then a cross-correlation between the process noise and the newly measurement noise is established. To eliminate the noise cross-correlation, a reconstructed process equation is proposed. According to the new process and measurement equations, and the noise mathematical characteristics of the standard Kalman filtering method, the parameters involved in the new process equation can be acquired. Then the noise cross-correlation can be successfully eliminated, and a decorrelation Kalman filtering model can be obtained. At the same time, for obtaining a more accurate measurement noise variance, an adaptive recursive algorithm is proposed to update the measurement noise variance based on the correlation method. It overcomes the limitations of traditional correlation methods used for noise variance estimation, thus, a relatively accurate Kalman filtering model can be obtained. The simulation shows that the proposed method improves the estimation accuracy of the motion state of object feature point.

The characterization of the Galactic foregrounds has been shown to be the main obstacle in thechallenging quest to detect primordial B-modes in the polarized microwave sky. We make use of the Planck-HFI 2015 data release at high frequencies to place new constraints on the properties of the polarized thermal dust emission at high Galactic latitudes. Here, we specifically study the spatial variability of the dust polarized spectral energy distribution (SED), and its potential impact on the determination of the tensor-to-scalar ratio, r. We use the correlation ratio of the CBBℓ angular power spectra between the 217 and 353 GHz channels as a tracer of these potential variations, computed on different high Galactic latitude regions, ranging from 80% to 20% of the sky. The new insight from Planck data is a departure of the correlation ratio from unity that cannot be attributed to a spurious decorrelation due to the cosmic microwave background, instrumental noise, or instrumental systematics. The effect is marginally detected on each region, but the statistical combination of all the regions gives more than 99% confidence for this variation in polarized dust properties. In addition, we show that the decorrelation increases when there is a decrease in the mean column density of the region of the sky being considered, and we propose a simple power-law empirical model for this dependence, which matches what is seen in the Planck data. We explore the effect that this measured decorrelation has on simulations of the BICEP2-Keck Array/Planck analysis and show that the 2015 constraints from these data still allow a decorrelation between the dust at 150 and 353 GHz that is compatible with our measured value. Finally, using simplified models, we show that either spatial variation of the dust SED or of the dust polarization angle are able to produce decorrelations between 217 and 353 GHz data similar to the values we observe in the data.