most citedKernel principal component analysis network for image classification

8 citations · 15 across the 7 of their papers we have counts for

collaborators

7 papers

cs.LG2015★ 8 cited

Kernel principal component analysis network for image classification

Dan Wu, Jiasong Wu, Rui Zeng +3

In order to classify the nonlinear feature with linear classifier and improve the classification accuracy, a deep learning network named kernel principal component analysis network…

eess.SY2015★ 1 cited

Error Gradient-based Variable-Lp Norm Constraint LMS Algorithm for Sparse System Identification

Yong Feng, Fei Chen, Rui Zeng +2

Sparse adaptive filtering has gained much attention due to its wide applicability in the field of signal processing. Among the main algorithm families, sparse norm constraint adapt…

eess.SY2015★ 4 cited

Gradient Compared Lp-LMS Algorithms for Sparse System Identification

Yong Feng, Jiasong Wu, Rui Zeng +2

In this paper, we propose two novel p-norm penalty least mean square (Lp-LMS) algorithms as supplements of the conventional Lp-LMS algorithm established for sparse adaptive filteri…

cs.CV2015★ 1 cited

Color Image Classification via Quaternion Principal Component Analysis Network

Rui Zeng, Jiasong Wu, Zhuhong Shao +3

The Principal Component Analysis Network (PCANet), which is one of the recently proposed deep learning architectures, achieves the state-of-the-art classification accuracy in vario…

eess.SY2015

p-norm-like Constraint Leaky LMS Algorithm for Sparse System Identification

Yong Feng, Rui Zeng, Jiasong Wu

In this paper, we propose a novel leaky least mean square (leaky LMS, LLMS) algorithm which employs a p-norm-like constraint to force the solution to be sparse in the application o…

eess.SY2015★ 1 cited

p Norm Constraint Leaky LMS Algorithm for Sparse System Identification

Yong Feng, Rui Zeng, Jiasong Wu

This paper proposes a new leaky least mean square (leaky LMS, LLMS) algorithm in which a norm penalty is introduced to force the solution to be sparse in the application of system…

cs.CV2014

Tensor object classification via multilinear discriminant analysis network

Rui Zeng, Jiasong Wu, Lotfi Senhadji +1

This paper proposes a multilinear discriminant analysis network (MLDANet) for the recognition of multidimensional objects, known as tensor objects. The MLDANet is a variation of li…