Biodiesel has the potential to significantly contribute to making transportation fuels more
sustainable. Due to the complexity and nonlinearity of processes for biodiesel production …

In this article, an iterative procedure is proposed for the training process of the probabilistic
neural network (PNN). In each stage of this procedure, the Q (0)-learning algorithm is …

The article is devoted to pattern recognition task with the database containing small number
of samples per class. By mapping of local continuous feature vectors to a discrete range, this …

In this article, a novel wavelet probabilistic neural network (WPNN), which is a generative-
learning wavelet neural network that relies on the wavelet-based estimation of class …

It is important to improve the classification accuracy and reduce the storage space when
probabilistic neural networks are used for pattern classification tasks. Based on a unit …

This works proposes IGMN (standing for Incremental Gaussian Mixture Network), a new
connectionist approach for incremental concept formation and robotic tasks. It is inspired on …

In this work we use IGMN (standing for incremental Gaussian mixture network), an
incremental neural network model based on Gaussian mixtures, for on-line control and …

The paper proposes an improved architecture for Probabilistic Neural Networks (IAPNN)
with an aggregation function based on f-mean of training patterns. The improved …

化学习的自学习和在线学习的特性决定了其非常适用于解决复杂的, 环境模型未知的,
不确定的时序决策优化问题. 随着强化学习理论研究的不断深入, 强化学习方法被越来越多地用 …

This paper presents a new probabilistic neural network model, called IPNN (for Incremental
Probabilistic Neural Network), which is able to learn continuously probability distributions …