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Iterative method of maximum likelihood for estimation of non-Gaussian probability density of signals and interferences) parameters to describe through a mixture of private probability densities. For definition of unknown
Deep Neural Networks for Emotion Recognition cell were used as models of deep neural networks. On their basis, an ensemble of neural networks
Bayesian analysis of the kinetics of quantal transmitter secretion at the neuromuscular junction of these is the exponentially modified Gaussian distribution. The mixture of normal and exponential components
Bayesian analysis of the kinetics of quantal transmitter secretion at the neuromuscular junction of these is the exponentially modified Gaussian distribution. The mixture of normal and exponential components
Emotions recognition in human speech with deep learning models as models of deep neural networks. An ensemble of neural networks was also built on their basis. Computer
Organization of innovative project management on the base of multimode modeling of probabilities mixture of labor processes modeling of probabilities mixture of labor processes. The proposed model allows managers to optimize
A Comprehensive Study of Density, Viscosity, and Electrical Conductivity of (Choline Chloride + Glycerol) Deep Eutectic Solvent and Its Mixtures with Dimethyl Sulfoxide) of a deep eutectic solvent (DES), glyceline, composed of choline chloride (ChCl) and glycerol at a 1
Dielectric relaxation of deep eutectic solvent + water mixtures: Structural implications and application to microwave heating© the Owner Societies. We studied the dielectric response of deep eutectic solvents (DESs) composed
Neural network analog of the ICP algorithm. For those tasks, it is more appropriate to use neural network technique and deep learning methods
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