Simulated annealing: theory and applications
Simulated annealing: theory and applications
Simulated annealing and Boltzmann machines: a stochastic approach to combinatorial optimization and neural computing
Pattern Classification (2nd Edition)
Pattern Classification (2nd Edition)
Biologically inspired self-adaptive multi-path routing in overlay networks
Communications of the ACM - Self managed systems
Comparison between coherent and noncoherent receivers for UWB communications
EURASIP Journal on Applied Signal Processing
Biologically inspired target recognition in radar sensor networks
EURASIP Journal on Wireless Communications and Networking - Special issue on wireless network algorithms, systems, and applications
Journal of Network and Computer Applications
All-purpose and plug-in power-law detectors for transient signals
IEEE Transactions on Signal Processing
IEEE Wireless Communications
Energy-Detection UWB Receivers with Multiple Energy Measurements
IEEE Transactions on Wireless Communications
Characterization of ultra-wide bandwidth wireless indoor channels: a communication-theoretic view
IEEE Journal on Selected Areas in Communications
Channel estimation for ultra-wideband communications
IEEE Journal on Selected Areas in Communications
The effects of timing jitter and tracking on the performance of impulse radio
IEEE Journal on Selected Areas in Communications
A Statistical Model for Indoor Multipath Propagation
IEEE Journal on Selected Areas in Communications
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Ultra-wideband (UWB) sensors have extensive commercial and military applications. Unfortunately, coherent signal detection in the presence of intensive multipath propagations may generally become impractical due to complicated realization algorithms and hardware requirements. In this article, we deal with noncoherent UWB signal detection within a promising biological framework, which can also be generalized to the binary-hypothesis target-detection problem, i.e. identification of the presence or absence of a target. Through the developed characteristic representations, signal detection is firstly formulated as a two-group pattern (or target) classification problem in a 2-D feature plane, in which an optimal decision bound can be numerically derived given the supervised training instances. This optimization problem is addressed by using the nature-inspired simulated annealing algorithm (SA), which essentially emulates the physical annealing process of forming the freeze state with the minimum energy. In sharp contrast to traditional optimization techniques, by probabilistically permitting search movement towards worse solutions, SA algorithm can converge to the global optimal with an asymptotical probability of 1. The numerically derived detection performance demonstrated that our present technique is much superior to the existing noncoherent schemes, which provides the appealing signal/target detection architecture for the emerging UWB sensor networks.