Humans flexibly weight incoming evidence when updating beliefs and adjusting behavior. In the current issue of Neuron, McGuire et al. (2014) show how distinct neuronal correlates of main factors underlying this weighting converge on a common mechanism driving belief updates.

this paper presents an overview of model updating and particularly its application for updating of frame model. in this article a mathematical model of the frame was produced with finite element method. the frame was subjected to hammer modal testing. then the results of the modal testing were compared with those predicted with the model. this comparison revealed discrepancies between these two...

Parallel Self-Organizing Map (Parallel-SOM) is proposed to modify Self-Organizing Map for parallel computing environments. In this model, the conventional repeated learning procedure is modified to learn just once. The once learning manner is more similar to human learning and memorizing activities. During training, every connection between neurons of input and output layers is considered as an...

We address an ensemble clustering problem, where reliable clusters are locally embedded in given multiple partitions. We propose a new nonnegative matrix factorization (NMF)-based method, in which locally reliable clusters are explicitly considered by using instance-wise weights over clusters. Our method factorizes the input cluster assignment matrix into two matrices H and W , which are optimi...

In this paper, a novel adaptive tracking controller is proposed for mobile robots in presence of wheel slip and external disturbance force based on neural networks with online weight updating laws. The uncertainties due to the wheel slip and external force are compensated online by neural networks in order to achieve the desired tracking performance. The online weight updating laws are modified...

This paper models an agent in a multi-period setting who does not update according to Bayes’ Rule, and who is self-aware and anticipates her updating behavior when formulating plans. Choice-theoretic axiomatic foundations are provided. Then the model is specialized axiomatically to capture updating biases that re‡ect excessive weight given to (i) prior beliefs, or alternatively, (ii) the realiz...

In 2006, Smith et al. published a new table of constant weight codes, updating existing tables originally created by Brouwer et al. This paper improves upon these results by filling in 9 missing constant weight codes, all of which are optimal by the second Johnson bound. This completes the tables for A(n, 16, 9) and A(n, 18, 10) up to n = 63 and corrects some A(n, 14, 8).