Improving the Quality of FPGA RO-PUF by Principal Component Analysis (PCA).
K. A. AshaLi En HsuAbhishek PatyalHung-Ming ChenPublished in: ACM J. Emerg. Technol. Comput. Syst. (2021)
Keyphrases
- principal component analysis
- principal components
- dimensionality reduction
- independent component analysis
- covariance matrix
- feature extraction
- low dimensional
- face recognition
- linear discriminant analysis
- dimension reduction
- feature space
- high quality
- singular value decomposition
- low cost
- face databases
- real time
- face images
- kernel pca
- discriminant analysis
- signal processing
- improve quality
- subspace learning
- fisher linear discriminant
- dimension reduction methods
- fpga implementation
- real time image processing
- training procedure
- lower dimensional
- quality assessment
- k means
- high speed