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EDICS
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EDICS
| Name | Description |
|---|
| ADEL | Adaptation, Detection, Estimation, and Learning |
|---|---|
| ADEL-DDE | Distributed detection and estimation |
| ADEL-DAN | Distributed adaptation over networks |
| ADEL-DLN | Distributed learning over networks |
| ADEL-DTT | Distributed target tracking |
| ADEL-BLSP | Bayesian learning; Bayesian signal processing |
| ADEL-SLN | Sequential learning over networks |
| ADEL-DMN | Decision making over networks |
| ADEL-DDL | Distributed dictionary learning |
| ADEL-DGTS | Distributed game theoretic strategies |
| ADEL-DIP | Distributed information processing |
| ADEL-GKM | Graphical and kernel methods |
| ADEL-CNS | Consensus over network systems |
| ADEL-ONS | Optimization over network systems |
| SIPG | Signal and Information Processing over Graphs |
|---|---|
| SIPG-DIS | Distributed processing of graph data |
| SIPG-STOC | Stochastic processes over graphs |
| SIPG-SAMP | Sampling, interpolation, denoising and reconstruction |
| SIPG-REP | Transforms, filtering, representation |
| SIPG-GCN | Graph convolutional neural networks |
| SIPG-APP | Applications |
| SIPG-MEND | Modeling and Estimation of Network Dynamics |
| SIPG-IDP | Information Diffusion and Propagation |
| SIPG-MNE | Modeling of Network Evolution |
| SIPG-GTOP | Graph learning and network topology inference |
| CNS | Communications, Networking, and Sensing |
|---|---|
| CNS-DMS | Distributed monitoring and sensing |
| CNS-SPDCN | Signal processing for distributed communications and networking |
| CNS-SPCN | Signal processing for cooperative networking |
| CNS-SPNS | Signal processing for network security |
| CNS-NSPRA | Optimal network signal processing and resource allocation |
| CNS-SQP | Scheduling and queuing protocols |
| CNS-CCMCT | Cooperative and coordinated multi-cell techniques |
| CNS-DSCD | Distributed source and channel decoding |
| CNS-ADHC | Ad-hoc wireless networks |
| CNS-APPL | Applications of sensor networks |
| CNS-ENGY | Energy efficient sensor network algorithms |
| CNS-LLC | Low latency communications |
| CNS-LOCL | Source localization in sensor networks |
| CNS-PHYL | Physical layer issues |
| CNS-FUSE | Data fusion from multiple sensors |
| CNS-CLRD | Cross-Layer design |
| CNS-RSMG | Resource management issues |
| CNS-SQUE | Scheduling and queuing protocols |
| CNS-SYLO | System level optimization |
| MA | Modeling and Analysis |
|---|---|
| MA-PBM | Performance and bounds of methods |
| MA-RV | Robustness and vulnerability |
| MA-NMI | Network modeling and identification |
| MA-SNIPS | Simulations of networked information processing systems |
| MA-SL | Social learning |
| MA-BNSP | Bio-inspired network signal processing |
| MA-EDP | Epidemics and diffusion in populations |
| IMA | Imaging and Media Applications |
|---|---|
| IMA-IVPN | Image and video processing over networks |
| IMA-MCCC | Media cloud computing and communication |
| IMA-MST | Multimedia streaming and transport |
| IMA-SMCN | Social media computing and networking |
| IMA-SPCPS | Signal processing for cyber-physical systems |
| IMA-WMM | Wireless/mobile multimedia |
| OTH | OTHER AREAS AND APPLICATIONS OF SIGNAL PROCESSING OVER NETWORKS |
|---|---|
| OTH-BGDT | Big Data |
| OTH-CPSY | Cyber-physical systems |
| OTH-ETOP | Emerging topics |
| OTH-IOT | Internet of things |
| OTH-CC | Crowd computing |
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