In this study, we evaluate the accuracy of classifiers for classification of ultrasonic liver tissues. Two different statistic classifiers ami three various artificial neural networks are included: Bayes classifier k-nearest neighbor classifier. Back-propagation neural networks, probabilistic neural network and modified probabilistic neural network. These Jive different classifiers were investi...

The objective of this paper is to analyze the practical viability of the results theoretical concerning the relationship of a class of weightless neural networks, known as General Single-layer Sequential Weightless Neural Networks (GSSWNNs), and Probabilistic Automata (PA). This study was based on the theoretical model development by de Souto [1]. This model shows the computational equivalence ...

BACKGROUND The neostriatum, the mouse homologue of the primate caudate/putamen, is the input nucleus for the basal ganglia, receiving both cortical and dopaminergic input to each of its sub-compartments, the striosomes and matrix. The coordinated activation of corticostriatal pathways is considered vital for motor and cognitive abilities, yet the mechanisms which underlie the generation of thes...

Building on earlier work extending Sigma’s mixed (symbols + probabilities) graphical band to inference in feedforward neural networks, two forms of neural network learning – target propagation and backpropagation – are introduced, bringing Sigma closer to a full neural-symbolic architecture. Adapting Sigma’s reinforcement learning (RL) capability to use neural networks in policy learning then y...

this article is a comparative study of estimation power of artificial neural networks and autoregressive time series models in inflation forecasting. using 37 years iran’s inflation data, neural networks performs better on average for short horizons than autoregressive models. this study shows usefulness of early stopping technique in learning stage of neural networks for estimating time series...

Perineuronal nets (PNNs) accumulate around neurons near the end of developmental critical periods. PNNs are structures of the extracellular matrix which surround synaptic contacts and contain chondroitin sulfate proteoglycans. Previous studies suggest that the chondroitin sulfate chains of PNNs inhibit synaptic plasticity and thereby help end critical periods. PNNs surround a high proportion of...

In this note we present and discuss results of experiments comparing the performance of six neural network architectures (back propagation, recurrent network with dampened feedback, network with multiple hidden layers each with a different activation function, jump connection networks, probabilistic neural networks and general regression neural networks) applied to a simplified multi-font recog...

Citation: Takeda A, Shuto M and Funakoshi K (2018) Chondroitin Sulfate Expression in Perineuronal Nets After Goldfish Spinal Cord Lesion. Front. Cell. Neurosci. 12:63. doi: 10.3389/fncel.2018.00063 Perineuronal nets (PNNs) surrounding neuronal cell bodies regulate neuronal plasticity during development, but their roles in regeneration are unclear. In the PNNs, chondroitin sulfate (CS) is assume...