STUDY OF NEURAL NETWORKS FOR CLUSTERING RADAR SIGNALS
- Authors
- Corporate Authors
- Ecole Polytechnique, Montreal QUE (CAN) Centre de Developpement Technologique;Defence Research Establishment Ottawa, Ottawa ONT (CAN)
- Abstract
- Self-organizing neural networks (SONN) are analyzed and compared for automatic deinterleaving of radar pulse streams in electronic support measures (ESM) applications. Theory behind existing SONNs is reviewed, and improvements are proposed for ESM use. Efficient and practical architectures for implementing these SONNs are proposed. This includes the design, simulation, fabriction and testing of proof-of-concept software, reconfigurable hardware, and an application specific integrated circuit (ASIC).
- Keywords
- Clustering;Self organizing;Unsupervised;Adaptive resonance theory;Reconfigurable hardware;Application Specific Integrated Circuits;ASIC;Deinterleaving
- Report Number
- C.D.T.-P19601;DREO-CR-98-610 — Contractor Report (Final)
- Date of publication
- 01 Mar 1998
- Number of Pages
- 187
- DSTKIM No
- 98-01925
- CANDIS No
- 508384
- Format(s):
- Hardcopy;Document Image stored on Optical Disk
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