Tuyển tập báo cáo các nghiên cứu khoa học quốc tế ngành hóa học dành cho các bạn yêu hóa học tham khảo đề tài: Research Article Biologically Inspired Target Recognition in Radar Sensor Networks | Hindawi Publishing Corporation EURASIP Journal on Wireless Communications and Networking Volume 2010 Article ID 523435 8 pages doi 2010 523435 Research Article Biologically Inspired Target Recognition in Radar Sensor Networks Qilian Liang Department of Electrical Engineering University of Texas at Arlington Arlington TX 76019-0016 USA Correspondence should be addressed to Qilian Liang liang@ Received 10 September 2009 Accepted 9 November 2009 Academic Editor Benyuan Liu Copyright 2010 Qilian Liang. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use distribution and reproduction in any medium provided the original work is properly cited. One of the great mysteries of the brain is cognitive control. How can the interactions between millions of neurons result in behavior that is coordinated and appears willful and voluntary There is consensus that it depends on the prefrontal cortex PFC . Many PFC areas receive converging inputs from at least two sensory modalities. Inspired by human s innate ability to process and integrate information from disparate network-based sources we apply human-inspired information integration mechanisms to target detection in cognitive radar sensor network. Humans information integration mechanisms have been modelled using maximum-likelihood estimation MLE or soft-max approaches. In this paper we apply these two algorithms to cognitive radar sensor networks target detection. Discrete-cosine-transform DCT is used to process the integrated data from MLE or soft-max. We apply fuzzy logic system FLS to automatic target detection based on the AC power values from DCT. Simulation results show that our MLE-DCT-FLS and soft-max-DCT-FLS approaches perform very well in the radar sensor network target detection whereas the existing 2D construction algorithm does not work in this study. 1. Introduction and Motivation Humans display a remarkable capability to perform .
