26,864 research outputs found
Distributed Binary Detection over Fading Channels: Cooperative and Parallel Architectures
This paper considers the problem of binary distributed detection of a known
signal in correlated Gaussian sensing noise in a wireless sensor network, where
the sensors are restricted to use likelihood ratio test (LRT), and communicate
with the fusion center (FC) over bandwidth-constrained channels that are
subject to fading and noise. To mitigate the deteriorating effect of fading
encountered in the conventional parallel fusion architecture, in which the
sensors directly communicate with the FC, we propose new fusion architectures
that enhance the detection performance, via harvesting cooperative gain
(so-called decision diversity gain). In particular, we propose: (i) cooperative
fusion architecture with Alamouti's space-time coding (STC) scheme at sensors,
(ii) cooperative fusion architecture with signal fusion at sensors, and (iii)
parallel fusion architecture with local threshold changing at sensors. For
these schemes, we derive the LRT and majority fusion rules at the FC, and
provide upper bounds on the average error probabilities for homogeneous
sensors, subject to uncorrelated Gaussian sensing noise, in terms of
signal-to-noise ratio (SNR) of communication and sensing channels. Our
simulation results indicate that, when the FC employs the LRT rule, unless for
low communication SNR and moderate/high sensing SNR, performance improvement is
feasible with the new fusion architectures. When the FC utilizes the majority
rule, such improvement is possible, unless for high sensing SNR
Filtering and control for unreliable communication: The discrete-time case
Copyright © 2014 Guoliang Wei et al. 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.In the past decades, communication networks have been extensively employed in many practical control systems, such as manufacturing plants, aircraft, and spacecraft to transmit information and control signals between the system components. When a control loop is closed via a serial communication channel, a networked control system (NCS) is formed. NCSs have become very popular for their great advantages over traditional systems (e.g., low cost, reduced weight, and power requirements, etc.). Generally, it has been implicitly assumed that the communication between the system components is perfect; that is, the signals transmitted from the plant always arrive at the filter or controller without any information loss. Unfortunately, such an assumption is not always true. For example, a common feature of the NCSs is the presence of significant network-induced delays and data losses across the networks. Therefore, an emerging research topic that has recently drawn much attention is how to cope with the effect of network-induced phenomena due to the unreliability of the network communication. This special issue aims at bringing together the latest approaches to understand, filter, and control for discrete-time systems under unreliable communication. Potential topics include but are not limited to (a) multiobjective filtering or control, (b) network-induced phenomena, (c) stability analysis, (d) robustness and fragility, and (e) applications in real-world discrete-time systems
Performance improvement in VSLAM using stabilized feature points
Simultaneous localization and mapping (SLAM) is the main prerequisite for the autonomy of a mobile robot. In this paper, we present a novel method that enhances the consistency of the map using stabilized corner features. The proposed method integrates template matching based video stabilization and Harris corner detector. Extracting Harris corner features from stabilized video consistently increases the accuracy of the localization. Data coming from a video camera and odometry are fused in an Extended Kalman Filter (EKF) to determine the pose of the robot and build the map of the environment. Simulation results validate the performance improvement obtained by the proposed technique
Landscape phage, phage display, stripped phage, biosensors, detection, affinity reagent, nanotechnology, Salmonella typhimurium, Bacillus anthracis
Filamentous phage, such as fd used in this study, are thread-shaped bacterial
viruses. Their outer coat is a tube formed by thousands equal copies of the
major coat protein pVIII. We constructed libraries of random peptides fused to
all pVIII domains and selected phages that act as probes specific for a panel
of test antigens and biological threat agents. Because the viral carrier is
infective, phage borne bio-selective probes can be cloned individually and
propagated indefinitely without needs of their chemical synthesis or
reconstructing. We demonstrated the feasibility of using landscape phages and
their stripped fusion proteins as new bioselective materials that combine
unique characteristics of affinity reagents and self assembling membrane
proteins. Biorecognition layers fabricated from phage-derived probes bind
biological agents and generate detectable signals. The performance of
phage-derived materials as biorecognition films was illustrated by detection of
streptavidin-coated beads, Bacillus anthracis spores and Salmonella typhimurium
cells. With further refinement, the phage-derived analytical platforms for
detecting and monitoring of numerous threat agents may be developed, since the
biodetector films may be obtained from landscape phages selected against any
bacteria, virus or toxin. As elements of field-use detectors, they are superior
to antibodies, since they are inexpensive, highly specific and strong binders,
resistant to high temperatures and environmental stresses.Comment: Submitted on behalf of TIMA Editions
(http://irevues.inist.fr/tima-editions
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