Advanced Randomized Neural Networks For Pattern Analysis
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A01=Chenglong Zhang
A01=David Zhang
A01=Shifei Ding
A01=Yang Wang
Advanced Randomized Neural Networks
Author_Chenglong Zhang
Author_David Zhang
Author_Shifei Ding
Author_Yang Wang
Category=UYQN
Category=UYQP
Cost-Sensitive Learning
Deep Ensemble Learning
Deep Stochastic Configuration Networks
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Evolutionary Ensemble Model
Fuzzy Neural Networks
Hyper-Parameter Optimization
Multi-Level Feature Fusion
Neural Networks Optimization
Parameter Greedy Searching
Robust Data Analysis
Sparse Representation Learning
Stochastic Configuration Networks
Uncertain Data Regression
Universal Approximation Property
Product details
- ISBN 9789819814688
- Publication Date: 04 Nov 2025
- Publisher: World Scientific Publishing Co Pte Ltd
- Publication City/Country: SG
- Product Form: Hardback
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This book is the culmination of our research in the recent decade on randomized neural networks with data-dependent supervision mechanisms. Traditional randomized neural networks mainly focused on constructing various deep neural networks with data independent random weights, ignoring the impact of the number of nodes and scope of parameters on the universal approximation property (UAP) of randomized neural networks. Comprising of 15 chapters, Advanced Randomized Neural Networks for Pattern Analysis introduces systematic solutions for advanced data-dependent stochastic configuration networks, namely algorithms that assign random parameters and construct network structures incrementally. The book is segmented into three major sections — neural networks optimization, robust data analysis, and deep fusion learning — that feature the successful performance of advanced randomized neural networks in various pattern analysis problems. We anticipate that both researchers and engineers in the field of artificial neural networks, particularly pattern recognition and medical diagnosis, will find this book and the associated algorithms useful, and we hope that anyone with an interest in the related research field will find the book enjoyable and informative.
