24,050 research outputs found
PI-BA Bundle Adjustment Acceleration on Embedded FPGAs with Co-observation Optimization
Bundle adjustment (BA) is a fundamental optimization technique used in many
crucial applications, including 3D scene reconstruction, robotic localization,
camera calibration, autonomous driving, space exploration, street view map
generation etc. Essentially, BA is a joint non-linear optimization problem, and
one which can consume a significant amount of time and power, especially for
large optimization problems. Previous approaches of optimizing BA performance
heavily rely on parallel processing or distributed computing, which trade
higher power consumption for higher performance. In this paper we propose
{\pi}-BA, the first hardware-software co-designed BA engine on an embedded
FPGA-SoC that exploits custom hardware for higher performance and power
efficiency. Specifically, based on our key observation that not all points
appear on all images in a BA problem, we designed and implemented a
Co-Observation Optimization technique to accelerate BA operations with
optimized usage of memory and computation resources. Experimental results
confirm that {\pi}-BA outperforms the existing software implementations in
terms of performance and power consumption.Comment: in Proceedings of IEEE FCCM 201
Temperature Dependence of the Effective Bag Constant and the Radius of a Nucleon in the Global Color Symmetry Model of QCD
We study the temperature dependence of the effective bag constant, the mass,
and the radius of a nucleon in the formalism of the simple global color
symmetry model in the Dyson-Schwinger equation approach of QCD with a
Gaussian-type effective gluon propagator. We obtain that, as the temperature is
lower than a critical value, the effective bag constant and the mass decrease
and the radius increases with the temperature increasing. As the critical
temperature is reached, the effective bag constant and the mass vanish and the
radius tends to infinity. At the same time, the chiral quark condensate
disappears. These phenomena indicate that the deconfinement and the chiral
symmetry restoration phase transitions can take place at high temperature. The
dependence of the critical temperature on the interaction strength parameter in
the effective gluon propagator of the approach is given.Comment: 10 pages, 9 figure
Event-Triggered Algorithms for Leader-Follower Consensus of Networked Euler-Lagrange Agents
This paper proposes three different distributed event-triggered control
algorithms to achieve leader-follower consensus for a network of Euler-Lagrange
agents. We firstly propose two model-independent algorithms for a subclass of
Euler-Lagrange agents without the vector of gravitational potential forces. By
model-independent, we mean that each agent can execute its algorithm with no
knowledge of the agent self-dynamics. A variable-gain algorithm is employed
when the sensing graph is undirected; algorithm parameters are selected in a
fully distributed manner with much greater flexibility compared to all previous
work concerning event-triggered consensus problems. When the sensing graph is
directed, a constant-gain algorithm is employed. The control gains must be
centrally designed to exceed several lower bounding inequalities which require
limited knowledge of bounds on the matrices describing the agent dynamics,
bounds on network topology information and bounds on the initial conditions.
When the Euler-Lagrange agents have dynamics which include the vector of
gravitational potential forces, an adaptive algorithm is proposed which
requires more information about the agent dynamics but can estimate uncertain
agent parameters.
For each algorithm, a trigger function is proposed to govern the event update
times. At each event, the controller is updated, which ensures that the control
input is piecewise constant and saves energy resources. We analyse each
controllers and trigger function and exclude Zeno behaviour. Extensive
simulations show 1) the advantages of our proposed trigger function as compared
to those in existing literature, and 2) the effectiveness of our proposed
controllers.Comment: Extended manuscript of journal submission, containing omitted proofs
and simulation
Multifractal analysis of weighted networks by a modified sandbox algorithm
Complex networks have attracted growing attention in many fields. As a
generalization of fractal analysis, multifractal analysis (MFA) is a useful way
to systematically describe the spatial heterogeneity of both theoretical and
experimental fractal patterns. Some algorithms for MFA of unweighted complex
networks have been proposed in the past a few years, including the sandbox (SB)
algorithm recently employed by our group. In this paper, a modified SB
algorithm (we call it SBw algorithm) is proposed for MFA of weighted
networks.First, we use the SBw algorithm to study the multifractal property of
two families of weighted fractal networks (WFNs): "Sierpinski" WFNs and "Cantor
dust" WFNs. We also discuss how the fractal dimension and generalized fractal
dimensions change with the edge-weights of the WFN. From the comparison between
the theoretical and numerical fractal dimensions of these networks, we can find
that the proposed SBw algorithm is efficient and feasible for MFA of weighted
networks. Then, we apply the SBw algorithm to study multifractal properties of
some real weighted networks ---collaboration networks. It is found that the
multifractality exists in these weighted networks, and is affected by their
edge-weights.Comment: 15 pages, 6 figures. Accepted for publication by Scientific Report
Symmetry Reduction and Boundary Modes for Fe-Chains on an s-wave Superconductor
We investigate the superconducting phase diagram and boundary modes for a
quasi-1D system formed by three Fe-Chains on an s-wave superconductor,
motivated by the recent Princeton experiment. The onsite
spin-orbit term, inter-chain diagonal hopping couplings, and magnetic disorders
in the Fe-chains are shown to be crucial for the superconducting phases, which
can be topologically trivial or nontrivial in different parameter regimes. For
the topological regime a single Majorana and multiple Andreew bound modes are
obtained in the ends of the chain, while for the trivial phase only low-energy
Andreev bound states survive. Nontrivial symmetry reduction mechanism induced
by the term, diagonal hopping couplings, and magnetic
disorder is uncovered to interpret the present results. Our study also implies
that the zero-bias peak observed in the recent experiment may or may not
reflect the Majorana zero modes in the end of the Fe-chains.Comment: 5 pages, 4 figures; some minor errors are correcte
Incentivizing High-quality Content from Heterogeneous Users: On the Existence of Nash Equilibrium
We study the existence of pure Nash equilibrium (PNE) for the mechanisms used
in Internet services (e.g., online reviews and question-answer websites) to
incentivize users to generate high-quality content. Most existing work assumes
that users are homogeneous and have the same ability. However, real-world users
are heterogeneous and their abilities can be very different from each other due
to their diverse background, culture, and profession. In this work, we consider
heterogeneous users with the following framework: (1) the users are
heterogeneous and each of them has a private type indicating the best quality
of the content she can generate; (2) there is a fixed amount of reward to
allocate to the participated users. Under this framework, we study the
existence of pure Nash equilibrium of several mechanisms composed by different
allocation rules, action spaces, and information settings. We prove the
existence of PNE for some mechanisms and the non-existence of PNE for some
mechanisms. We also discuss how to find a PNE for those mechanisms with PNE
either through a constructive way or a search algorithm
- β¦