Feed-forward neural networks have been used for pattern recognition, because they have an ability to estimate a posteriori probability.
Feed-forward neural networks have been used for pattern recognition, because they have an ability to estimate u posteriori probability. This paper investi-.
Seiichi Nakagawa, Yoshiyuki Ono: Estimation of the probability density function and a posteriori probability by neural networks, and applications to vowel ...
This paper proposes a novel algorithm to jointly determine the structure and the parameters of a posteriori probability model based on neural networks (NNs). It ...
MultiLayer Perceptrons (MLP) are an effective family of algorithms for the smooth estimation of highly-dimensioned probability density functions that are useful ...
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May 21, 2018 · Strictly speaking, neural networks are fitting a non-linear function. They can be interpreted as fitting a probability density function if suitable activation ...
Jan 18, 2023 · A method is presented for combining the feature extraction power of neural networks with model based dimensionality reduction to produce linguistically ...
A Neural Network Approach to Statistical Pattern. Classification by "Semiparametric" Estimation of Probability Density Functions. Hans G. C. Tråvén. Abstract ...
Discriminant functions formed by (a) probability-density-function (PDF), (b) posterior-probability, and (c) boundary-forming classifiers for a problem with ...
Jun 11, 2017 · Put simply, and without any mathematical symbols, prior means initial beliefs about an event in terms of probability distribution.