Signal Processing Theory and Methods Technical Committee

SPTM TC EDICS, effective August 1, 2006

1 Sampling and Reconstruction
1.1 Sampling theory and methods
1.2 Quantization
1.3 Extrapolation and interpolation
1.4 Signal reconstruction, restoration and enhancement
1.5 Multidimensional sampling and reconstruction

2 Signal and System Modeling, Representation and Estimation
2.1 System modeling: theory, performance analysis
2.2 Signal and noise modeling: theory, performance analysis
2.3 System identification and approximation
2.4 Multidimensional systems
2.5 Non-stationary signals and time-varying systems
2.6 Time-frequency and time-scale analysis
2.7 Blind and semi-blind source separation

3 Statistical Signal Processing
3.1 Detection and estimation theory and methods
3.2 Classification and pattern recognition
3.3 Cyclostationary signal analysis
3.4 Higher-order and fractional lower-order statistical methods
3.5 Performance analysis and bounds
3.6 Spectrum estimation theory and methods
3.7 Robust methods
3.8 Independent component analysis
3.9 Monte-Carlo based signal processing methods

4 Adaptive Signal Processing
4.1 Adaptive filter analysis and design
4.2 Fast algorithms for adaptive filtering
4.3 Frequency-domain and transform-based adaptive filtering
4.4 Sequential decision theory and methods
4.5 Performance analysis and bounds
4.6 Distributed and collaborative signal processing

5 Nonlinear Systems and Signal Processing
5.1 Median, rank-order and stack type filters
5.2 Non-Gaussian distribution filters
5.3 Nonlinear signal and system models
5.4 Nonlinear random process models
5.5 Nonlinear adaptive filters

6 Filter Design
6.1 Filter design criteria and optimization methods
6.2 Filter architectures
6.3 Performance analysis

7 Multirate Signal Processing
7.1 Multirate architectures
7.2 Filterbanks and wavelets
7.3 Multirate processing and multiresolution methods
7.4 Hierarchical models and tree-structured signal processing