87 citations · 159 across the 9 of their papers we have counts for
10 papers
Hierarchical Modes Exploring in Generative Adversarial Networks
Mengxiao Hu, Jinlong Li, Maolin Hu +1
In conditional Generative Adversarial Networks (cGANs), when two different initial noises are concatenated with the same conditional information, the distance between their outputs…
A Radio Signal Modulation Recognition Algorithm Based on Residual Networks and Attention Mechanisms
Ruisen Luo, Tao Hu, Zuodong Tang +3
To solve the problem of inaccurate recognition of types of communication signal modulation, a RNN neural network recognition algorithm combining residual block network with attenti…
A Hebbian/Anti-Hebbian Neural Network for Linear Subspace Learning: A Derivation from Multidimensional Scaling of Streaming Data
Cengiz Pehlevan, Tao Hu, Dmitri B. Chklovskii
Neural network models of early sensory processing typically reduce the dimensionality of streaming input data. Such networks learn the principal subspace, in the sense of principal…
A Hebbian/Anti-Hebbian Network for Online Sparse Dictionary Learning Derived from Symmetric Matrix Factorization
Tao Hu, Cengiz Pehlevan, Dmitri B. Chklovskii
Olshausen and Field (OF) proposed that neural computations in the primary visual cortex (V1) can be partially modeled by sparse dictionary learning. By minimizing the regularized r…
A Neuron as a Signal Processing Device
Tao Hu, Zaid J. Towfic, Cengiz Pehlevan +2
A neuron is a basic physiological and computational unit of the brain. While much is known about the physiological properties of a neuron, its computational role is poorly understo…
Online computation of sparse representations of time varying stimuli using a biologically motivated neural network
Tao Hu, Dmitri B. Chklovskii
Natural stimuli are highly redundant, possessing significant spatial and temporal correlations. While sparse coding has been proposed as an efficient strategy employed by neural sy…