Topic
White noise
About: White noise is a research topic. Over the lifetime, 16496 publications have been published within this topic receiving 318633 citations.
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TL;DR: These results show that in each case the high signal-to-noise maximum-likelihood rules have a performance nearly equal to that of the maximum- likelihood rules over a wide range of practically interesting signal- to- noise ratios (SNR's).
Abstract: The problem of locating a periodically inserted frame synchronization pattern in random data for a M -ary digital communication system operating over the additive white Gaussian noise channel is considered. The optimum maximum-likelihood decision rule, high signal-to-noise approximate maximum likelihood decision rule, and ordinary correlation decision rule for frame synchronization are derived for both coherent and noncoherent phase demodulation. A general lower bound on synchronization probability is derived for the coherent correlation rule. Monte Carlo computer simulations of all three decision rules, along with evaluations of the lower bound for the coherent correlation rule, were performed for the coherent MPSK, coherent, and noncoherent M ary orthogonal, and 16 QAM signaling schemes. These results show that in each case the high signal-to-noise maximum-likelihood rules have a performance nearly equal to that of the maximum-likelihood rules over a wide range of practically interesting signal-to-noise ratios (SNR's). These high SNR decision rules also provide significant performance improvement over the simple correlation rules. Moreover, they are much simpler to implement than the maximum-likelihood decision rules and, in fact, are no more complex than the correlation rules.
138 citations
TL;DR: 1/f noise is tied directly to a probability limit distribution and a second mechanism involving scaling is introduced to provide a natural crossover from log-normal to inverse power-law behavior and generates 1/fα noise instead of pure 1/ f noise.
Abstract: A generic mechanism for the ubiquitous phenomenon of 1/f noise is reviewed. This mechanism arises in random processes expressible as a product of several random variables. Under mild conditions this product form leads to the log-normal distribution which we show straightforwardly generates 1/f noise. Thus, 1/f noise is tied directly to a probability limit distribution. A second mechanism involving scaling is introduced to provide a natural crossover from log-normal to inverse power-law behavior and generates 1/fα noise instead of pure 1/f noise. Examples of these distributions and the transitions between them are drawn from such diverse areas as economics, scientific productivity, bronchial structure and cardiac activity.
137 citations
TL;DR: In this paper, the authors consider parabolic stochastic partial differential equations driven by white noise in time and prove exponential convergence of the transition probabilities towards a unique invariant measure under suitable conditions.
Abstract: We consider parabolic stochastic partial differential equations driven by white noise in time. We prove exponential convergence of the transition probabilities towards a unique invariant measure under suitable conditions. These conditions amount essentially to the fact that the equation transmits the noise to all its determining modes. Several examples are investigated, including some where the noise does not act on every determining mode directly.
137 citations
TL;DR: The relationship between two well-known techniques in hyperspectral image detection and classification: orthogonal subspace projection (OSP) and constrained energy minimization is investigated and it is shown that they are closely related and essentially equivalent provided that the noise is white with large SNR.
Abstract: We conduct a comparative study and investigate the relationship between two well-known techniques in hyperspectral image detection and classification: orthogonal subspace projection (OSP) and constrained energy minimization. It is shown that they are closely related and essentially equivalent provided that the noise is white with large SNR. Based on this relationship, the performance of OSP can be improved via data-whitening and noise-whitening processes.
137 citations
Book•
01 Jan 2000
TL;DR: In this article, the authors present a model of continuous-time signals as sum of Discrete-Time Sine Waves, where the signal is modelled as a sum of sine waves.
Abstract: The Nature of Biomedical Signals. Memory and Correlation. The Impulse Response. Frequency Response. Modeling Continuous-Time Signals as Sums of Sine Waves. Responses of Linear Continuous-Time Filters to Arbitrary Inputs. Modeling Signals as Sums of Discrete-Time Sine Waves. Noise Removal and Signal Compensation. Modeling Stochastic Signals as Filtered White Noise. Scaling and Long-Term Memory. Nonlinear Models of Signals. Assessing Stationarity and Reproducibility. Appendix.
137 citations