Subspace fitting via sparse representation of signal covariance for DOA estimation.
Chundi ZhengGang LiYoucai LiPublished in: ICASSP (2016)
Keyphrases
- sparse representation
- doa estimation
- signal subspace
- direction of arrival
- subspace learning
- correlation matrix
- compressive sensing
- high dimensional data
- signal processing
- dimensionality reduction
- basis vectors
- sparse coding
- dictionary learning
- canonical correlation analysis
- orthogonal matching pursuit
- compressed sensing
- face recognition
- image classification
- random projections
- covariance matrix
- image patches
- high dimensional
- joint optimization
- sound source
- negative matrix factorization
- low dimensional
- feature extraction
- estimation error
- sensor array
- singular value decomposition
- sparse coefficients
- data analysis
- least squares
- principal component analysis
- image data
- feature space
- natural images
- high dimensionality
- pattern recognition
- neural network
- signal to noise ratio