Noise and Sampling
Variational blue noise sampling
... Blue Noise Sampling Zhonggui Chen, Zhan Yuan, Yi-King Choi, Ligang Liu, and Wenping Wang Abstract—Blue noise point sampling is one of the core algorithms in computer ...blue noise ...
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Microstructure noise, realized volatility, and optimal sampling
... the noise distribution. The second moment of the noise process is, of course, not an ...unobserved noise-in-return ...the noise process in that it will be a necessary input to formulate an ...
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Circuit Noise Interference on Sampling Clock and Its Effect on A/D Conversion
... However, all of these investigations were based on the assumption of ideal A/D converssion environment, the clock jitter is Gaussian-noise-only. Although it’s highly recommended to avoid this assumption, generally ...
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Enhancement of Noise Performance in Digital Receivers by Over Sampling the Received Signal
... over- sampling the received signal is similar to the pro- cess gain that is achieved in DSSS-BPSK ...channel noise will be sampled by the same rate, so more than one sample of the noise will be taken ...
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Noise Contrastive Estimation and Negative Sampling for Conditional Models: Consistency and Statistical Efficiency
... Noise Contrastive Estimation (NCE) is a pow- erful parameter estimation method for log- linear models, which avoids calculation of the partition function or its derivatives at each training step, a computationally ...
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A Good Sample is Hard to Find: Noise Injection Sampling and Self Training for Neural Language Generation Models
... 9 Conclusion We present a novel self-training methodology for learning DNN-based dialogue generation mod- els using noise injection sampling and a MR parser. Even with relatively simple architectures and ...
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Draft Field Sampling Plan Traffic and Noise Monitoring at Area IV Santa Susana Field Laboratory Ventura County, California
... field sampling event, the Task Leader, with the assistance of the Deputy Task Leader, will verify that all written data collected in the field is entered into an electronic format, ensure that all data undergoes ...
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Bring Back the Noise: How Cariou v. Prince Will Revitalize Sampling
... On the other hand, some commentators argue that there is no evidence that sampling licenses stifle creativity. 78 This argument is counterfactual, since it is impossible to ascertain what music would sound like if ...
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Interference-plus-Noise Covariance Matrix Reconstruction via Spatial Power Spectrum Sampling for Robust Adaptive Beamforming
... Inspired by the sampling and reconstruction idea, in this paper, a novel method named spatial power spectrum sampling SPSS is proposed to reconstruct the INC matrix more efficiently, wit[r] ...
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SAMPLING LINEAR INVERSE PROBLEMS WITH NOISE
... about noise and inverse ...Using noise a source for a reconstruction has been studied in [1, 2, 7, ...about sampling in the semiclassical ...white noise is uniform, by computing its microlocal ...
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Optimal sampling for simulated annealing under noise
... This paper proposes a Simulated Annealing variant for optimization problems in which the solution quality can only be estimated by sampling from a random distribution. The aim is to find the solution with the best ...
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An exploration of improving sampling within Monte Carlo ray tracing using adaptive blue noise.
... Chapter 1 Introduction “Random number generation is too important to be left to chance” – Robert Coveyou Ray tracing is a very popular, if not the most popular method to use in the field of image synthesis. This ...
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Volatility Decomposition and Nonparametric Estimation of Spot Volatility of Models with Poisson Sampling under Market Microstructure Noise
... microstructure noise we have to adapt an estimator from diffusion models to our situation which can cope successfully with mi- crostructure ...Many noise-robust estima- tors have therefore been introduced ...
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Sparsely sampling the sky: Regular vs. random sampling
... sparse sampling ap- proach was investigated in a previous paper (Paykari & Jaffe 2013), where the advantages and disadvantages of such a de- sign was ...sparse sampling could be a powerful substitute for the ...
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Sparsely sampling the sky: regular vs. random sampling
... sparse sampling ap- proach was investigated in a previous paper (Paykari & Jaffe 2013), where the advantages and disadvantages of such a de- sign was ...sparse sampling could be a powerful substitute for the ...
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The sampling brain
... any sampling algorithm that draws independent samples from the posterior distribution, such as DS, because the sample sequence would have no serial correlation ...to sampling from multimodal ...
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Decision by sampling
... Table 2 shows that the numerical values assigned to many probability phrases are quite variable. This finding is well established in the literature (see Budescu & Wallsten,1995). Thus, the positioning of each probability ...
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Moderate deviations principle and importance sampling for slow-fast diffusions with small noise
... importance sampling (IS) may offer a useful ...importance sampling works very well when it can be implemented, MD-based IS schemes turn out to work equally well for events that are moderately rare and are ...
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Stack Sampling Stack sampling or source sampling
... • Determination of the traverse point required for a velocity and temperature profile across the cross section of the stack and sampling for particulate matter... Schematic Diagram – Sam[r] ...
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Sampling and Sampling Distributions
... Other Sampling Designs Simple random sampling is the most natural and easily understood method of probability sampling — it corresponds to our intuitive notion of random selection by ...random ...
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