AIMC Journal:
IEEE transactions on neural networks and learning systems

Showing 631 to 640 of 817 articles

Symmetric Predictive Estimator for Biologically Plausible Neural Learning.

IEEE transactions on neural networks and learning systems Oct 25, 2017
In a real brain, the act of perception is a bidirectional process, depending on both feedforward sensory pathways and feedback pathways that carry expectations. We are interested in how such a neural network might emerge from a biologically plausible...
Deep Learning Models, Neurological Forecasting Brain Humans Neural Networks, Computer
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A Distance-Based Weighted Undersampling Scheme for Support Vector Machines and its Application to Imbalanced Classification.

IEEE transactions on neural networks and learning systems Oct 25, 2017
A support vector machine (SVM) plays a prominent role in classic machine learning, especially classification and regression. Through its structural risk minimization, it has enjoyed a good reputation in effectively reducing overfitting, avoiding dime...
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A Deep Machine Learning Method for Classifying Cyclic Time Series of Biological Signals Using Time-Growing Neural Network.

IEEE transactions on neural networks and learning systems Oct 12, 2017
This paper presents a novel method for learning the cyclic contents of stochastic time series: the deep time-growing neural network (DTGNN). The DTGNN combines supervised and unsupervised methods in different levels of learning for an enhanced perfor...
Respiratory Mechanics Interrupted Time Series Analysis Machine Learning Heart Rate Humans Neural Networks, Computer
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Detection of Sources in Non-Negative Blind Source Separation by Minimum Description Length Criterion.

IEEE transactions on neural networks and learning systems Oct 3, 2017
While non-negative blind source separation (nBSS) has found many successful applications in science and engineering, model order selection, determining the number of sources, remains a critical yet unresolved problem. Various model order selection me...
Databases, Factual Computer Simulation Neural Networks, Computer Monte Carlo Method Machine Learning
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Deep Manifold Learning Combined With Convolutional Neural Networks for Action Recognition.

IEEE transactions on neural networks and learning systems Sep 15, 2017
Learning deep representations have been applied in action recognition widely. However, there have been a few investigations on how to utilize the structural manifold information among different action videos to enhance the recognition accuracy and ef...
Machine Learning Deep Learning Humans Neural Networks, Computer Movement Photic Stimulation Video Recording Pattern Recognition, Automated
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Stability Analysis of Genetic Regulatory Networks With Switching Parameters and Time Delays.

IEEE transactions on neural networks and learning systems Jun 28, 2017
This paper is concerned with the exponential stability analysis of genetic regulatory networks (GRNs) with switching parameters and time delays. In this paper, a new integral inequality and an improved reciprocally convex combination inequality are c...
Neural Networks, Computer Algorithms Computer Simulation Time Factors Humans Gene Regulatory Networks
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Time-Varying System Identification Using an Ultra-Orthogonal Forward Regression and Multiwavelet Basis Functions With Applications to EEG.

IEEE transactions on neural networks and learning systems Jun 22, 2017
A new parametric approach is proposed for nonlinear and nonstationary system identification based on a time-varying nonlinear autoregressive with exogenous input (TV-NARX) model. The TV coefficients of the TV-NARX model are expanded using multiwavele...
Computer Simulation Time Factors Nonlinear Dynamics Neural Networks, Computer Electroencephalography Humans Brain Waves Algorithms
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Driving Under the Influence (of Language).

IEEE transactions on neural networks and learning systems Jun 9, 2017
We present a unified framework which supports grounding natural-language semantics in robotic driving. This framework supports acquisition (learning grounded meanings of nouns and prepositions from human sentential annotation of robotic driving paths...
Robotics Language Semantics Learning Comprehension Humans Driving Under the Influence Neural Networks, Computer
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Learning to Predict Consequences as a Method of Knowledge Transfer in Reinforcement Learning.

IEEE transactions on neural networks and learning systems Apr 17, 2017
The reinforcement learning (RL) paradigm allows agents to solve tasks through trial-and-error learning. To be capable of efficient, long-term learning, RL agents should be able to apply knowledge gained in the past to new tasks they may encounter in ...
Transfer, Psychology Reinforcement, Psychology Spatial Navigation Humans Predictive Value of Tests Algorithms Neural Networks, Computer Knowledge Computer Simulation
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State Estimation for Delayed Genetic Regulatory Networks With Reaction-Diffusion Terms.

IEEE transactions on neural networks and learning systems Nov 14, 2016
This paper addresses the problem of state estimation for delayed genetic regulatory networks (DGRNs) with reaction-diffusion terms using Dirichlet boundary conditions. The nonlinear regulation function of DGRNs is assumed to exhibit the Hill form. Th...
Time Factors Models, Theoretical Algorithms Gene Regulatory Networks Computational Biology Humans Animals Diffusion Models, Genetic Neural Networks, Computer
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