A feedforward neural network defines a mapping from an input x to an output y through a function f of x and theta. For example, we use neural networks to produce outputs such as the location of all cars in a camera image. The function f takes an input x, and uses a set of learned...
1.In this paper, a systematic analysis is made on the global optimization of multilayerfeedforward neural network, some fundamental conditions which need be met by any algorithm of global optimization are presented, a practicable algorithm of global optimization is suggested and reasonableness and valid...
Basic definitions concerning the multi-layer feed-forward neural networks are given. The back-propagation training algorithm is explained. Partial derivati... D Svozil,V Kvasnicka,Jirí Pospichal - 《Chemometrics & Intelligent Laboratory Systems》 被引量: 680发表: 1997年 Artificial Bee Colony (ABC)...
the noise levels, etc. Recognition accuracy can be explained well by different models. However, most models paid no attention to the processing time, and the ones which do, are not biologically
When we use a feedforward neural network to accept an inputx xxand produce an outputy ^ \hat{\boldsymbol{y}}y^, information flows forward through the network. The inputsx \boldsymbol{x}xprovide the initial information that then propagates up to the hidden units at each layer and fi...
unsupervised hyperspheric multilayer feedforward neural network classifierBiological system modelingThis paper introduces a novel Neural Network (NN) model intended to classification of patterns into distinct categories. Arbitrary accurate category formation in a predefined feature space is asymptotically achieved...
1 A “feed-forward” network is any neural network in which the data flows in one direction (i.e., from input to output). By this definition, the perceptron is also a “feed-forward” model, but usually the term is reserved for more complicated models with multiple units. 2 In ...
Is there a standard and accepted method for selecting the number of layers, and the number of nodes in each layer, in a feed-forward neural network? I'm interested in automated ways of building neural networks. model-selection neural-networks Share Cite Improve this quest...
Sensory processing is distributed among many brain regions that interact via feedforward and feedback signaling. Neuronal oscillations have been shown to mediate intercortical feedforward and feedback interactions. Yet, the macroscopic structure of the m
While some of the functional differences can be explained by differential feedforward retinal input such as cortical magnification factor (Banks et al., 1991; Yu et al., 2010), some functional properties such as spatial integration (Nurminen et al., 2018) are perhaps controlled by differential ...