Dimensionality Reduction for Signal Detection.
Steven KayPublished in: IEEE Signal Process. Lett. (2022)
Keyphrases
- signal detection
- dimensionality reduction
- pattern recognition
- principal component analysis
- high dimensional
- weak signal
- data points
- high dimensional data
- data representation
- input space
- low signal to noise ratio
- low dimensional
- high dimensionality
- structure preserving
- feature extraction
- preprocessing step
- linear discriminant analysis
- feature selection
- euclidean distance
- feature space
- nonlinear dimensionality reduction
- pattern recognition and machine learning
- dimensionality reduction methods
- principal components
- intrinsic dimensionality
- random projections
- metric learning
- kernel pca
- manifold learning
- dimension reduction
- singular value decomposition
- supervised dimensionality reduction
- neural network
- diffusion maps
- support vector machine
- linear dimensionality reduction
- linear projection
- artificial intelligence
- machine learning