4 citations · 13 across the 14 of their papers we have counts for
14 papers
Low-Memory Implementations of Ridge Solutions for Broad Learning System with Incremental Learning
Hufei Zhu
The existing low-memory BLS implementation proposed recently avoids the need for storing and inverting large matrices, to achieve efficient usage of memories. However, the existing…
Efficient and Stable Algorithms to Extend Greville's Method to Partitioned Matrices Based on Inverse Cholesky Factorization
Hufei Zhu
Greville's method has been utilized in (Broad Learn-ing System) BLS to propose an effective and efficient incremental learning system without retraining the whole network from the…
Efficient Inverse-Free Incremental and Decremental Algorithms for Multiple Hidden Nodes in Extreme Learning Machine
Hufei Zhu
The inverse-free extreme learning machine (ELM) algorithm proposed in [4] was based on an inverse-free algorithm to compute the regularized pseudo-inverse, which was deduced from a…
Comments on "Low-Complexity SIC Detection Algorithms for Multiple-Input Multiple-Output Systems"
Hufei Zhu, Yanpeng Wu
In the above paper, the optimal-ordered successive interference cancellation (SIC) detector proposed for multiple input multiple output (MIMO) systems was claimed to require a lowe…
An Improved Square-root Algorithm for V-BLAST Based on Efficient Inverse Cholesky Factorization
Hufei Zhu, Wen Chen, Bin Li +1
A fast algorithm for inverse Cholesky factorization is proposed, to compute a triangular square-root of the estimation error covariance matrix for Vertical Bell Laboratories Layere…
A Fast Recursive Algorithm for G-STBC
Hufei Zhu, Wen Chen, Bin Li +1
This paper proposes a fast recursive algorithm for Group-wise Space-Time Block Code (G-STBC), which takes full advantage of the Alamouti structure in the equivalent channel matrix…
Comments on "A New ML Based Interference Cancellation Technique for Layered Space-Time Codes"
Hufei Zhu, Wen Chen
In this comment, we justify that the computational complexity proposed in the paper "A New ML Based Interference Cancellation Technique for Layered Space-Time Codes" (IEEE Trans. o…
Complexity Comparison between Two Optimal-Ordered SIC MIMO Detectors Based on Matlab Simulations
Yanpeng Wu, Hufei Zhu
This paper firstly introduces our shared Matlab source code that simulates the two optimal-ordered SIC detectors proposed in [1] and [2]. Based on our shared Matlab code, we compar…
Efficient Decremental Learning Algorithms for Broad Learning System
Hufei Zhu
The decremented learning algorithms are required in machine learning, to prune redundant nodes and remove obsolete inline training samples. In this paper, an efficient decremented…
Inverse LDM' and LU Factorizations of a Partitioned Matrix with the Square-root and Division Free Version for V-BLAST
Hufei Zhu
This letter proposes the inverse LDM' and LU factorizations of a matrix partitioned into 2x2 blocks, which include the square-root and division free version. The proposed squareroo…
Efficient Inverse-Free Algorithms for Extreme Learning Machine Based on the Recursive Matrix Inverse and the Inverse LDL' Factorization
Hufei Zhu, Chenghao Wei
The inverse-free extreme learning machine (ELM) algorithm proposed in [4] was based on an inverse-free algorithm to compute the regularized pseudo-inverse, which was deduced from a…
Two Efficient Ridge Solutions for the Incremental Broad Learning System on Added Inputs
Hufei Zhu
This paper proposes the recursive and square-root BLS algorithms to improve the original BLS for new added inputs, which utilize the inverse and inverse Cholesky factor of the Herm…
Two Ridge Solutions for the Incremental Broad Learning System on Added Nodes
Hufei Zhu
The original Broad Learning System (BLS) on new added nodes and its existing efficient implementation both assume the ridge parameter lambda -> 0 in the ridge inverse to approximat…
Reducing the Computational Complexity of Pseudoinverse for the Incremental Broad Learning System on Added Inputs
Hufei Zhu, Zhulin Liu, C. L. Philip Chen +1
In this brief, we improve the Broad Learning System (BLS) [7] by reducing the computational complexity of the incremental learning for added inputs. We utilize the inverse of a sum…