[go: up one dir, main page]

Davenport, 2010 - Google Patents

Random observations on random observations: Sparse signal acquisition and processing

Davenport, 2010

View PDF
Document ID
10420835904128029979
Author
Davenport M
Publication year

External Links

Snippet

In recent years, signal processing has come under mounting pressure to accommodate the increasingly high-dimensional raw data generated by modern sensing systems. Despite extraordinary advances in computational power, processing the signals produced in …
Continue reading at mdav.ece.gatech.edu (PDF) (other versions)

Classifications

    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04NPICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N19/00Methods or arrangements for coding, decoding, compressing or decompressing digital video signals
    • H04N19/60Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using transform coding
    • H04N19/63Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using transform coding using sub-band based transform, e.g. wavelets
    • H04N19/635Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using transform coding using sub-band based transform, e.g. wavelets characterised by filter definition or implementation details
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06FELECTRICAL DIGITAL DATA PROCESSING
    • G06F17/00Digital computing or data processing equipment or methods, specially adapted for specific functions
    • G06F17/10Complex mathematical operations
    • G06F17/14Fourier, Walsh or analogous domain transformations, e.g. Laplace, Hilbert, Karhunen-Loeve, transforms

Similar Documents

Publication Publication Date Title
Davenport Random observations on random observations: Sparse signal acquisition and processing
Willett et al. Sparsity and structure in hyperspectral imaging: Sensing, reconstruction, and target detection
Duarte et al. Structured compressed sensing: From theory to applications
Rani et al. A systematic review of compressive sensing: Concepts, implementations and applications
Davenport et al. Introduction to compressed sensing.
Baraniuk A lecture on compressive sensing
Baraniuk Compressive sensing [lecture notes]
Baraniuk et al. An introduction to compressive sensing
US7511643B2 (en) Method and apparatus for distributed compressed sensing
US8725784B2 (en) Method and apparatus for compressive domain filtering and interference cancellation
Jacques et al. CMOS compressed imaging by random convolution
Lu et al. Sampling signals from a union of subspaces
Zhao et al. Image compressive-sensing recovery using structured laplacian sparsity in DCT domain and multi-hypothesis prediction
Hegde et al. Sampling and recovery of pulse streams
CN104660269B (en) A kind of perception matrix generating method perceived for Signal Compression
Orchard et al. Real time compressive sensing video reconstruction in hardware
Sevak et al. CT image compression using compressive sensing and wavelet transform
Ashwini et al. Compressive sensing based simultaneous fusion and compression of multi-focus images using learned dictionary
Candes et al. People hearing without listening: An introduction to compressive sampling
Bi et al. Image compressed sensing based on wavelet transform in contourlet domain
Siddamal et al. A survey on compressive sensing
Desai et al. Compressive sensing in speech processing: A survey based on sparsity and sensing matrix
Shahriar et al. Image reconstruction via compressed sensing
Satyan the use of compressive Sensing in Video
Kundu et al. Sparse signal recovery from nonadaptive linear measurements