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  2. Additive noise differential privacy mechanisms - Wikipedia

    en.wikipedia.org/wiki/Additive_noise...

    Adding controlled noise from predetermined distributions is a way of designing differentially private mechanisms. This technique is useful for designing private mechanisms for real-valued functions on sensitive data. Some commonly used distributions for adding noise include Laplace and Gaussian distributions.

  3. Additive white Gaussian noise - Wikipedia

    en.wikipedia.org/wiki/Additive_white_Gaussian_noise

    Gaussian because it has a normal distribution in the time domain with an average time domain value of zero (Gaussian process). Wideband noise comes from many natural noise sources, such as the thermal vibrations of atoms in conductors (referred to as thermal noise or Johnson–Nyquist noise ), shot noise , black-body radiation from the earth ...

  4. Linear–quadratic–Gaussian control - Wikipedia

    en.wikipedia.org/wiki/Linear–quadratic...

    It concerns linear systems driven by additive white Gaussian noise. The problem is to determine an output feedback law that is optimal in the sense of minimizing the expected value of a quadratic cost criterion. Output measurements are assumed to be corrupted by Gaussian noise and the initial state, likewise, is assumed to be a Gaussian random ...

  5. Gaussian noise - Wikipedia

    en.wikipedia.org/wiki/Gaussian_noise

    In signal processing theory, Gaussian noise, named after Carl Friedrich Gauss, is a kind of signal noise that has a probability density function (pdf) equal to that of the normal distribution (which is also known as the Gaussian distribution). [1] [2] In other words, the values that the noise can take are Gaussian-distributed.

  6. White noise analysis - Wikipedia

    en.wikipedia.org/wiki/White_noise_analysis

    First, white noise is a generalized stochastic process with independent values at each time. [12] Hence it plays the role of a generalized system of independent coordinates, in the sense that in various contexts it has been fruitful to express more general processes occurring e.g. in engineering or mathematical finance, in terms of white noise.

  7. Diffusion model - Wikipedia

    en.wikipedia.org/wiki/Diffusion_model

    These typically involve training a neural network to sequentially denoise images blurred with Gaussian noise. [2] [5] The model is trained to reverse the process of adding noise to an image. After training to convergence, it can be used for image generation by starting with an image composed of random noise, and applying the network iteratively ...

  8. Noise-predictive maximum-likelihood detection - Wikipedia

    en.wikipedia.org/wiki/Noise-predictive_maximum...

    Thus, the concept of noise prediction for stationary Gaussian noise sources developed in [2] [6] can be naturally extended to the case where noise characteristics depend highly on local data patterns. [1] [10] [11] [12] By modeling the data-dependent noise as a finite-order Markov process, the optimum MLSE for channels with ISI has been derived ...

  9. White noise - Wikipedia

    en.wikipedia.org/wiki/White_noise

    On the other hand, the sh sound /ʃ/ in ash is a colored noise because it has a formant structure. In music and acoustics, the term white noise may be used for any signal that has a similar hissing sound. In the context of phylogenetically based statistical methods, the term white noise can refer to a lack of phylogenetic pattern in comparative ...