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Combining negative selection and classification techniques for anomaly detection
TLDR
A novel approach inspired by the immune system that allows the application of conventional classification algorithms to perform anomaly detection and produces fuzzy characterization of the normal (or abnormal) space.
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Beyond Feedforward Models Trained by Backpropagation: A Practical Training Tool for a More Efficient Universal Approximator
TLDR
This work implemented a generic cellular SRN (CSRN) and applied it for solving two challenging problems: 2-D maze navigation and a subset of the connectedness problem, and superior generalization has been demonstrated in the case of connectedness.
View on IEEE
Unsupervised Learning with Self-Organizing Spiking Neural Networks
TLDR
A hybridization of self-organized map properties with spiking neural networks that retain many of the features of SOMs is presented, and using the optimal choice of parameters, this approach produces improvements over state-of-art spiking Neural networks.
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BindsNET: A Machine Learning-Oriented Spiking Neural Networks Library in Python
TLDR
It is argued that this package facilitates the use of spiking networks for large-scale machine learning problems and some simple examples by using BindsNET in practice are shown.
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Phase transitions in the neuropercolation model of neural populations with mixed local and non-local interactions
TLDR
The role of non-local (axonal) connections in generating and modulating phase transitions of collective activity in the neuropil is investigated and a relationship between critical values of the noise level and non-locality parameter to control the onset of phase transitions is derived.
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Breathing as a Fundamental Rhythm of Brain Function
TLDR
It is argued that respiration, via multiple sensory pathways, contributes a rhythmic component to the ongoing cortical activity and is suggested that this rhythmic activity modulates the temporal organization of cortical neurodynamics, thereby linking higher cortical functions to the process of breathing.
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Advances in Neuromorphic Memristor Science and Applications
Physical implementation of the memristor at industrial scale sparked the interest from various disciplines, ranging from physics, nanotechnology, electrical engineering, neuroscience, to intelligent…
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Cellular SRN Trained by Extended Kalman Filter Shows Promise for ADP
TLDR
This work improves the previous results by training the cellular simultaneous recurrent neural network with extended Kalman filter (EKF), the original EKF algorithm has been slightly modified.
View on IEEE
Chaotic Resonance - Methods and Applications for Robust Classification of noisy and Variable Patterns
TLDR
A theory of stochastic chaos is developed, in which aperiodic outputs with 1/f2 spectra are formed by the interaction of globally connected nodes that are individually governed by point attractors under perturbation by continuous white noise.
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Complete stability analysis of a heuristic approximate dynamic programming control design
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