Topic
White noise
About: White noise is a research topic. Over the lifetime, 16496 publications have been published within this topic receiving 318633 citations.
Papers published on a yearly basis
Papers
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TL;DR: An effective method is proposed for the estimation of the signal subspace dimension which is able to operate against colored noise with performances superior to those exhibited by the classical information theoretic criteria of Akaike and Rissanen.
Abstract: In order to operate properly, the superresolution methods based on orthogonal subspace decomposition, such as multiple signal classification (MUSIC) or estimation of signal parameters by rotational invariance techniques (ESPRIT), need accurate estimation of the signal subspace dimension, that is, of the number of harmonic components that are superimposed and corrupted by noise. This estimation is particularly difficult when the S/N ratio is low and the statistical properties of the noise are unknown. Moreover, in some applications such as radar imagery, it is very important to avoid underestimation of the number of harmonic components which are associated to the target scattering centers. In this paper, we propose an effective method for the estimation of the signal subspace dimension which is able to operate against colored noise with performances superior to those exhibited by the classical information theoretic criteria of Akaike and Rissanen. The capabilities of the new method are demonstrated through computer simulations and it is proved that compared to three other methods it carries out the best trade-off from four points of view, S/N ratio in white noise, frequency band of colored noise, dynamic range of the harmonic component amplitudes, and computing time.
66 citations
TL;DR: The Magnetic anomaly detection method is expanded to the more general case of magnetic noise with a power spectral density of 1/fα, where 0 is the power spectraldensity of Gaussian white noise.
Abstract: Magnetic anomaly detection (MAD) is a passive method for detection of a ferromagnetic target A magnetic field generated by a ferromagnetic target is assumed as a dipole field, resulting in an anomaly in the ambient Earth magnetic field Magnetic anomaly detection method using orthonormal basis functions (OBF) decomposition is a known approach The method, which relies on matched filtering, should be optimal for detection of a known signal in the presence of Gaussian white noise In this work, we expand the method to the more general case of magnetic noise with a power spectral density of 1/fα, where 0
66 citations
TL;DR: Conditions for uniform asymptotic stability in the large of the optimal minimum mean square error linear filter are developed for linear systems whose observations are corrupted by white multiplicative noise in addition to white additive noise.
Abstract: Conditions for uniform asymptotic stability in the large of the optimal minimum mean-square error linear filter are developed for linear systems whose observations are corrupted by white multiplicative noise in addition to white additive noise. Both discrete-time as well as continuous-time systems are considered. The multiplicative noise model may be useful in problems associated with phenomena such as fading, or reflection of the transmitted signal from the ionosphere, and also certain situations involving sampling, gating, or amplitude modulation. Conditions for existence, uniqueness, and stability of the steady-state optimal filter are also considered for time-invariant systems.
66 citations
TL;DR: A new mechanism generating long range temporal correlations in dynamical systems coupled to a source of white noise is discussed, and both Poisson statistics for events in log(time) and the 1/f power spectrum are found.
Abstract: We discuss a new mechanism generating long range temporal correlations in dynamical systems coupled to a source of white noise. The external noise induces dynamical events uncorrelated on a logarithmic time scale and produces a fluctuating output with ``1/f'' power spectrum. This behavior requires a complex phase space with many traps, which can arise due to strong cooperative effects. As a demonstration, we numerically analyze a system of many coupled degrees of freedom, which is externally driven and subject to a white noise perturbation. We find both Poisson statistics for events in log(time) and the 1/f power spectrum.
66 citations
TL;DR: A wide frequency range is divided into multiple subbands and in each subband detect whether in a primary user (PU) is active or not and an invariant generalized likelihood ratio (GLR) detector is proposed.
Abstract: In this paper, we divide a wide frequency range into multiple subbands and in each subband detect whether in a primary user (PU) is active or not. We assume that PU signal at each subband and the additive noise are white zero-mean independent Gaussian random processes with unknown variances. We also assume that at least a minimum given number of subbands is vacant of PU signal and propose an invariant generalized likelihood ratio (GLR) detector. The concept of the grouping of subbands allows faster spectrum sensing of a subset of subbands which may be occupied by a specific PU. Also, we evaluate trade-offs involved in the proposed algorithms by simulation.
66 citations