Adaptive Fusion of Kernels for Radial Basis Function Neural Network
In this algorithm the two popular similarity measures, Cosine distance (angle) and Euclidean distance are fused together and the mixing weight is made adaptive using gradient decent algorithm. The submission is the example for pattern recognition problem utilized in the paper [1].
Reference
[1] http://link.springer.com/article/10.1007/s00034-016-0375-7
% @article{khan2016novel,
% title={A Novel Adaptive Kernel for the RBF Neural Networks},
% author={Khan, Shujaat and Naseem, Imran and Togneri, Roberto and Bennamoun, Mohammed},
% journal={Circuits, Systems, and Signal Processing},
% pages={1--15},
% year={2016},
% publisher={Springer US}
% }
引用格式
Shujaat Khan (2024). Adaptive Fusion of Kernels for Radial Basis Function Neural Network (https://www.mathworks.com/matlabcentral/fileexchange/59001-adaptive-fusion-of-kernels-for-radial-basis-function-neural-network), MATLAB Central File Exchange. 检索来源 .
MATLAB 版本兼容性
平台兼容性
Windows macOS Linux类别
- AI, Data Science, and Statistics > Deep Learning Toolbox > Image Data Workflows > Pattern Recognition and Classification >
标签
Community Treasure Hunt
Find the treasures in MATLAB Central and discover how the community can help you!
Start Hunting!Pattern_Recognition_Using_NAK_RBF/
版本 | 已发布 | 发行说明 | |
---|---|---|---|
1.0.0.0 |