نتایج جستجو برای: perceptrons
تعداد نتایج: 1707 فیلتر نتایج به سال:
Human emotion recognition is an important issue in human–computer interactions, and electroencephalograph (EEG) has been widely applied to due its high reliability. In recent years, methods based on deep learning technology have reached the state-of-the-art performance EEG-based recognition. However, there exist singularities parameter space of neural networks, which may dramatically slow down ...
This paper presents a method for massively parallel learning of part-of-speech disambiguation based on a minmax modular neural network model. The method has three main steps. Firstly, a large-scale tagging problem is decomposed into a number of relatively smaller and simpler subproblems according to the class relations among a given training corpus. Secondly, all of the subproblems are learned ...
OBJECTIVE The main goal of this paper is to obtain a classification model based on feed-forward multilayer perceptrons in order to improve postpartum depression prediction during the 32 weeks after childbirth with a high sensitivity and specificity and to develop a tool to be integrated in a decision support system for clinicians. MATERIALS AND METHODS Multilayer perceptrons were trained on d...
In the neural network/genetic algorithm community, rather limited success in the training of neural networks by genetic algorithms has been reported. In a paper by Whitley et al. (1991), he claims that, due to "the multiple representations problem", genetic algorithms will not effectively be able to train multilayer perceptrons, whose chromosomal representation of its weights exceeds 300 bits. ...
There are three papers in a series of discussions related to the partitioning capabilities on nested rectangular decision regions using multi-layer perceptrons. We propose a constructive algorithm, called the up-down algorithm, to realize the nested rectangular decision regions. The algorithm determines the weights easily and can be generalized to solve other decision regions with the propertie...
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