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The minimum regret path problem on stochastic fuzzy time-varying networks.

Neural networks : the official journal of the International Neural Network Society
In this paper, we introduce a stochastic fuzzy time-varying minimum regret path problem (SFTMRP), which combines the characteristics of the min-max regret path and maximum probability path as a variant of the stochastic fuzzy time-varying shortest pa...

Cardinality-constrained portfolio selection via two-timescale duplex neurodynamic optimization.

Neural networks : the official journal of the International Neural Network Society
This paper addresses portfolio selection based on neurodynamic optimization. The portfolio selection problem is formulated as a biconvex optimization problem with a variable weight in the Markowitz risk-return framework. In addition, the cardinality-...

Multimodal Orbital Angular Momentum Data Model Based on Mechanically Reconfigurable Arrays and Neural Networks.

Computational intelligence and neuroscience
Multimodal orbital angular momentum is a research hotspot in the field of electromagnetic wave communication. How to accurately detect and identify multimodal orbital angular momentum data is a current academic problem. Based on the theory of mechani...

Sequence learning, prediction, and replay in networks of spiking neurons.

PLoS computational biology
Sequence learning, prediction and replay have been proposed to constitute the universal computations performed by the neocortex. The Hierarchical Temporal Memory (HTM) algorithm realizes these forms of computation. It learns sequences in an unsupervi...

Error-based or target-based? A unified framework for learning in recurrent spiking networks.

PLoS computational biology
The field of recurrent neural networks is over-populated by a variety of proposed learning rules and protocols. The scope of this work is to define a generalized framework, to move a step forward towards the unification of this fragmented scenario. I...

Codimension-2 parameter space structure of continuous-time recurrent neural networks.

Biological cybernetics
If we are ever to move beyond the study of isolated special cases in theoretical neuroscience, we need to develop more general theories of neural circuits over a given neural model. The present paper considers this challenge in the context of continu...

Face identity coding in the deep neural network and primate brain.

Communications biology
A central challenge in face perception research is to understand how neurons encode face identities. This challenge has not been met largely due to the lack of simultaneous access to the entire face processing neural network and the lack of a compreh...

A framework for the general design and computation of hybrid neural networks.

Nature communications
There is a growing trend to design hybrid neural networks (HNNs) by combining spiking neural networks and artificial neural networks to leverage the strengths of both. Here, we propose a framework for general design and computation of HNNs by introdu...

Maximum entropy models provide functional connectivity estimates in neural networks.

Scientific reports
Tools to estimate brain connectivity offer the potential to enhance our understanding of brain functioning. The behavior of neuronal networks, including functional connectivity and induced connectivity changes by external stimuli, can be studied usin...

SepNet: A neural network for directionally correlated data.

Neural networks : the official journal of the International Neural Network Society
Multi-dimensional tensor data appear in diverse settings, including multichannel signals, spectrograms, and hyperspectral data from remote sensing. In many cases, these data are directionally correlated, i.e. the correlation between variables from di...