different frequencies, weighting, using the hardware-based noise generator, amplitudes of the plurality of periodic waveforms based on a predetermined spectral shape to form a plurality of weighted waveforms, and summing the plurality of plurality of weighted waveforms to form an output random noise ...
Fractional Gaussian noise criterion for correlations characterization: a random-matrix-theory inspired perspectiveDMACalorimetryChemorheologyMechanical propertiesCuringThermosets characterizationWe introduce a particular construction of an autocorrelation matrix of a timeseries and its analysis based on the random-...
网络高斯随机噪声;高斯随机杂讯 网络释义
目标是maximize某个probability(比如MLE maximizes log likelihood,即max probability of data given parameter,算是把data看成有概率的而parameter是确定性的;MAP maximizes a posterior是max prob of parameter given data,考虑的是后验概率,明显的贝叶斯思想,一切、包括参数在内、都是random的)。
[124] proposed the weighted even moment (WEM) algorithm for adaptive filtering based on the linear combination of the even moments of the error. However, LMF algorithm suffers from the stability problem, as its stability strongly depends on the initial weight values along with noise and input po...
2022 TGRS Seismic Random Noise Attenuation Based on Non-IID Pixel-Wise Gaussian Noise Modeling. VI-non-IID can explicitly predict both the latent clean data and the pixelwise noise level map ($\bf{\sigma}$) - mengchuangji/VI-Non-IID
This paper describes the recognition method of random mass patterns corrupted by additive Gaussian noise. In our previous papers this method was applied to the recognition of abnormal shadows in chest roentgenograms and found to work effectively. In this paper we theoretically study the method from...
aussian white noise Adaptive filtering of a random signal in Gaussian white noiseAdaptive filtering of a random signal in Gaussian white noiseBelitserE. N.EnikeevaF. N.PROBLEMS OF INFORMATION TRANSMISSION C/C OF PROBLEMY PEREDACHI INFORMATSII...
Furthermore, the background and foreground models are used competitively in a MAP-MRF (Maximum A Posteriori Markov Random Field) [192] decision framework. A sequential KDE algorithm is presented in [228]. • Support vector models: The second category uses more sophisticated statistical models ...
This paper describes and analyses some methods of generating pseudorandom sequences suitable for use in the simulation of white Gaussian noise. The criteria are somewhat different than those customary in pseudorandom number generation in other applications such as Monte Carlo methods. The methods ...