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Signal Processing Theory and Methods

Technical Committee

EDICS

NOTE: The Technical Committee's EDICS list is derived from the Society's Unified EDICS list. You can view the Society's complete Unified EDICS ist and EDICS list approval process on the Unified EDICS page.

 

SMDSP SAMPLING, MULTIRATE SIGNAL PROCESSING AND DIGITAL SIGNAL PROCESSING
SMDSP-SAM Sampling, Theory, Analysis and Methods
SMDSP-CNS Compressed and Nonuniform Sampling
SMDSP-RECO Algorithms for signal filtering, restoration, enhancement, and reconstruction
SMDSP-MRA Multiresolution Analysis, filter banks, and wavelets
SMDSP-FAT Fast Algorithms and Transforms
SMDSP-SAP Sparsity-aware processing
SIPG Signal and Information Processing over Graphs
SIPG-SA Statistical Approaches (models, etc.)
SIPG-DA Deterministic Approaches (graph filtering, graph transforms, etc.)
SIPG-GRA Graph Representations and Analysis
SIPG-AL Adaptation and Learning Over Graphs
OPT Optimization Methods for Signal Processing
OPT-CVXR Convex optimization and relaxation for SP
OPT-DOPT Distributed optimization for SP
OPT-NCVX Non-convex methods for SP
OPT-SPARSE Sparse optimization techniques for SP
OTH-QUAN Quantum signal processing
ASP Adaptive Signal Processing
ASP-ANAL Adaptive filter analysis and design
ASP-APPL Applications of adaptive filters
ASP-FAST Fast algorithms for adaptive filtering
ASP-FREQ Frequency-domain and subband adaptive filtering
SSP Statistical Signal Processing
SSP-ANA Analysis
SSP-APPL Applications of statistical signal processing techniques
SSP-BSP Bayesian signal processing
SSP-CLAS Classification methods
SSP-DTM Detection Theory and Methods
SSP-ETM Estimation Theory and Methods
SSP-LNSP Linear and Nonlinear Systems and Signal Processing
SSP-MM Models and Methods
SSP-TRAC Tracking algorithms
DPON Signal Processing over Networks
DPON Distributed Processing and Optimization over Networks
EDLN Estimation, Detection and Learning over Networks
NEG-APPL Applications of sensor networks
SMDSP-SAP Sparsity-aware Processing; Sparse/low-dimensional signal recovery, parameter estimation and regression; Structured matrix factorization, low-rank models, matrix completion; Dictionary learning; subspace and manifold learning

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