AIMC Topic: Neural Networks, Computer

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Quaternion Projection Rule for Rotor Hopfield Neural Networks.

IEEE transactions on neural networks and learning systems
A rotor Hopfield neural network (RHNN) is an extension of a complex-valued Hopfield neural network (CHNN) and has excellent noise tolerance. The RHNN decomposition theorem says that an RHNN decomposes into a CHNN and a symmetric CHNN. For a large num...

Dynamical Channel Pruning by Conditional Accuracy Change for Deep Neural Networks.

IEEE transactions on neural networks and learning systems
Channel pruning is an effective technique that has been widely applied to deep neural network compression. However, many existing methods prune from a pretrained model, thus resulting in repetitious pruning and fine-tuning processes. In this article,...

Random Sketching for Neural Networks With ReLU.

IEEE transactions on neural networks and learning systems
Training neural networks is recently a hot topic in machine learning due to its great success in many applications. Since the neural networks' training usually involves a highly nonconvex optimization problem, it is difficult to design optimization a...

Deep Coattention-Based Comparator for Relative Representation Learning in Person Re-Identification.

IEEE transactions on neural networks and learning systems
Person re-identification (re-ID) favors discriminative representations over unseen shots to recognize identities in disjoint camera views. Effective methods are developed via pair-wise similarity learning to detect a fixed set of region features, whi...

Quaternion-Valued Twin-Multistate Hopfield Neural Networks With Dual Connections.

IEEE transactions on neural networks and learning systems
Dual connections (DCs) utilize the noncommutativity of quaternions and improve the noise tolerance of quaternion Hopfield neural networks (QHNNs). In this article, we introduce DCs to twin-multistate QHNNs. We conduct computer simulations to investig...

Adaptive Neural Control for a Class of Nonlinear Multiagent Systems.

IEEE transactions on neural networks and learning systems
This article studies the adaptive neural controller design for a class of uncertain multiagent systems described by ordinary differential equations (ODEs) and beams. Three kinds of agent models are considered in this study, i.e., beams, nonlinear ODE...

Robust Environmental Sound Recognition With Sparse Key-Point Encoding and Efficient Multispike Learning.

IEEE transactions on neural networks and learning systems
The capability for environmental sound recognition (ESR) can determine the fitness of individuals in a way to avoid dangers or pursue opportunities when critical sound events occur. It still remains mysterious about the fundamental principles of biol...

Assessing Dry Weight of Hemodialysis Patients via Sparse Laplacian Regularized RVFL Neural Network with L-Norm.

BioMed research international
Dry weight is the normal weight of hemodialysis patients after hemodialysis. If the amount of water in diabetes is too much (during hemodialysis), the patient will experience hypotension and shock symptoms. Therefore, the correct assessment of the pa...

Explaining mobile government social media continuance from the valence perspective: A SEM-NN approach.

PloS one
Different from many previous studies explain mobile social media usage from a technical-center perspective, the present study investigates the factors that influence citizens' mobile government social media (GSM) continuance based on the valence fram...

Artificial Intelligence in the assessment of diabetic retinopathy from fundus photographs.

Seminars in ophthalmology
: Over the next 25 years, the global prevalence of diabetes is expected to grow to affect 700 million individuals. Consequently, an unprecedented number of patients will be at risk for vision loss from diabetic eye disease. This demand will almost ce...