multilayered neural networkpositive correlation learningWe propose a training algorithm for multi-layered neural-network (NN) classifiers that improves the generalization ability, the ability to classify previously unseen patterns. A correlation term was added to the error function of the standard back-...
Cognitive psychology Components of the Neural Valuation Network of Monetary Rewards THE OHIO STATE UNIVERSITY John Opfer KanayetFrank JosephWhen faced with a decision between goods with incommensurable values, the chooser needs to rescale the valuation assigned to each good in a common mental ...
It tests a neuralnetwork with a wide range of confusing real-world inputs and tells the network whenits responses are wrong so that t can correct itself. For example, DeepXplore coulddetermine if a camera image fed to a car-driving AI system mistakenly steered a vehicletoward pedestrians. ...
Forward propagation is a key process in various types of neural networks, each with its own architecture and specific steps involved in moving input data through the network to produce an output. Forward propagation is a fundamental process in various types of neural networks, including: ...
Neuronal aggregates involved in conscious awareness are not evenly distributed throughout the CNS but comprise key components referred to as the neural network correlates of consciousness (NNCC). A critical node in this network is the posterior cingulate, precuneal, and retrosplenial cortices. The ...
The neural network, using an unsupervised generalized Hebbian algorithm (GHA), is adopted to find the principal eigenvectors of a covariance matrix in different kinds of seismograms. We have shown that the extensive computer results of the principal components analysis (PCA) using the neural net of...
Using these features as input, a two-layered back-propagation neural network is built and trained to sort vehicles into five classes. In this regard, availability of the video images provides essential information for developing the needed labeled datasets. The trained network is tested, and ...
In the case of a stationary environment, the neural nets can develop a deep understanding of the problem and working in a properly chosen, narrow subspace of the system variables. In this functional mode, a small number of parameters dominate the operation of the network on the surface (...
Institutional Access International Journal of Neural SystemsVol. 01, No. 01, pp. 61-68 (1989) No Access Erkki Oja https://doi.org/10.1142/S0129065789000475Cited by:625(Source: Crossref) Previous Next PDF/EPUB Tools Share Cite Recommend ...
They also resemble the receptive fields of simple cells in visual cortex, which suggests that these neurons form a natural, information-theoretic coordinate system for natural images. 展开 关键词: Information theory Independent components Neural network learning ...