Two new distributed speed advisory systems (SASs) are introduced in this paper. The systems implement consensus algorithms that guide a set of vehicles toward a common driving speed. A major innovation is that consens...
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Two new distributed speed advisory systems (SASs) are introduced in this paper. The systems implement consensus algorithms that guide a set of vehicles toward a common driving speed. A major innovation is that consensus is achieved over a multi-layer network, in which parallel network topologies of connected vehicles are superimposed. The reason for the use of these parallel networks is that, in this way, the state obfuscation is possible, with the benefit that common driving speed is attained with no vehicle knowing the exact state of other vehicles. Convergence of the SASs is formally proved and two new results for the consensus of multi-layer networks modeled via stochastic differential equations are introduced. The SASs are also validated via simulation and via a hardware-in-the-loop setup, in which a real vehicle interacts with simulated entities.
This paper is concerned with integrated target search, tasking and tracking using multiple fixed-wing UAVs. The problem is to design control logic and plan the flight paths for UAVs. The fixed-wing UAVs are required t...
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ISBN:
(纸本)9781479928378
This paper is concerned with integrated target search, tasking and tracking using multiple fixed-wing UAVs. The problem is to design control logic and plan the flight paths for UAVs. The fixed-wing UAVs are required to cooperatively search the potential targets and keep monitoring the found targets according to a predefined minimal revisit time. Each UAV can only communicate with its neighbors and also flight autonomy is designed for individual UAVs. Decentralized target search, task assignment and target tracking algorithms are developed and evaluated by simulations using a real miniature fixed-wing UAV model.
In this paper we consider the pair-wise sequence alignment problem with gaps, which is motivated by the re sequencing problem that requires to assemble short reads sequences into a genome sequence by referring to a re...
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ISBN:
(纸本)9781467365987
In this paper we consider the pair-wise sequence alignment problem with gaps, which is motivated by the re sequencing problem that requires to assemble short reads sequences into a genome sequence by referring to a reference sequence. The problem has been studied before for single gap and bounded number of gaps. For single gap, there was a GPU-based algorithm proposed. In our work we propose a GPU-based algorithm for the bounded number of gaps case. We implemented the algorithm and compare the performance with the CPU-based algorithm in a multithreadded environment;the results are promising with the GPU version achieving a speedup of 30 times.
Optimal design is intractable in general. We identify a tractable class of design problems and propose the first framework for efficient, decision-theoretically optimal, collaborative design.
ISBN:
(纸本)9780769530277
Optimal design is intractable in general. We identify a tractable class of design problems and propose the first framework for efficient, decision-theoretically optimal, collaborative design.
The algorithms used in wireless applications are increasingly more sophisticated and consequently more challenging to implement in hardware. Traditional design flows require developing the micro architecture, coding t...
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ISBN:
(纸本)0769522882
The algorithms used in wireless applications are increasingly more sophisticated and consequently more challenging to implement in hardware. Traditional design flows require developing the micro architecture, coding the RTL, and verifying the generated RTL against the original functional C or MATLAB specification. This paper describes a C-based design flow that is well suited for the hardware implementation of DSP algorithms commonly found in wireless applications. The C design flow relies on guided synthesis to generate the RTL directly from the untimed C algorithm. The specifics of the C-based design flow are described using a simple DSP filtering algorithm consisting of a forward adaptive equalizer, a 64-QAM slicer and an adaptive decision feedback equalizer The example illustrates some of the capabilities and advantages offered by this flow.
The importance of automatic algorithms design has been pointed out by researchers. In general, automatically designed algorithms can outperform tailored made ones. This is the case of the Particle Swarm Optimization a...
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ISBN:
(纸本)9781538624074
The importance of automatic algorithms design has been pointed out by researchers. In general, automatically designed algorithms can outperform tailored made ones. This is the case of the Particle Swarm Optimization algorithm (PSO) that has many components that can be chosen such as the velocity equation, etc. Motivated by the success reported by the automatic design of the PSO, this study investigates Multi-objective PSO (MOPSO), an extension of PSO that deals with multi-objective problems. Furthermore, this study presents a framework based on the use of a context-free grammar to guide the design of the MOPSO. The grammar allows the use of different components and parameters from various MOPSOs. Further, the framework offers two design methods: Grammatical Evolution (GE) and Iterated Race (IRACE). Likewise, a set of experiments is made to evaluate the framework using a set of Multi-objective problems, quality indicators and statistical tests. The set of experiments includes the evaluation of: two versions of the grammar, GE against IRACE and a comparison with the Speed-constrained PSO (SMPSO), a well-known multi-objective algorithm.
The space-based precipitation products are commonly used for regional and/or global hydrologic modelling and climate studies. However, the accuracy of onboard satellite measurements is limited due to the spatial tempo...
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ISBN:
(纸本)9789082598704
The space-based precipitation products are commonly used for regional and/or global hydrologic modelling and climate studies. However, the accuracy of onboard satellite measurements is limited due to the spatial temporal sampling limitations, especially for extreme events such as very heavy or light rain. On the other hand, ground-based radar is more mature science for quantitative precipitation estimation (QPE). Nowadays, ground radars are critical for providing local scale rainfall estimation for operational forecasters to issue watches and warnings, as well as validation of various space measurements and products. This paper introduces a neural network based data fusion mechanism to improve satellite-based precipitation retrievals by incorporating dual-polarization measurements from ground-based dense radar network. The prototype architecture of this fusion system is detailed. Results from urban scale application in Dallas-Fort Worth (DFW) Metroplex are presented.
Particle filter algorithm has a unique advantage in dealing with nonlinear, non-Gaussian state estimation. Particle filter method cannot accurately estimate the state of the system due to the particle degeneration and...
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ISBN:
(纸本)9781509043644
Particle filter algorithm has a unique advantage in dealing with nonlinear, non-Gaussian state estimation. Particle filter method cannot accurately estimate the state of the system due to the particle degeneration and lack of particle diversity. In this paper, we propose a new particle filter algorithm called "Gauss based auxiliary particle filter" that introduces the real-time observation information into the importance probability density function. During resampling step, the particles are redistributed using Gaussian transformation and the weights of the particles after resampling are adjusted. The simulation results illustrate that the proposed method can effectively use the current values and optimize the particle distribution. This algorithm cannot only solve the problem of particle degeneration, but it can also maintain the diversity of particles and improve the filter efficiency.
作者：
Yi, HwangFlorida Int Univ
Dept Architecture Coll Commun Architecture Arts 11200 SW 8th St Miami FL 33199 USA
The author seeks a practical approach to complement deterministic design optimization in environmental performance-based building design. This study investigates algorithms and scripted processes to test and monitor t...
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ISBN:
(纸本)9781538634288
The author seeks a practical approach to complement deterministic design optimization in environmental performance-based building design. This study investigates algorithms and scripted processes to test and monitor the dynamic optimal control of building components. To this end, an integration of wireless data transfer equipment (nRF24L01) and a customized metaheuristic hybrid optimization algorithm (Tabubased adaptive pattern search simulated annealing, T-APSSA) through a parametric visual programming language (VPL) interface (Rhino grasshopper (R)) is presented with experimental design of a responsive kinetic shading device. To demonstrate the performance of the algorithmic hybridization and early design integration, T-APSSA is compared to simulated annealing and pattern (direct) search, and two different approaches to daylight-optimized design solutions are tested: a deterministic optimization based on historical weather data and a site-specific adaptive optimization according to real-time monitoring of incident solar radiance. The suggestion of a seamless environmental building design workflow through remote data communication contributes to strengthening intelligent architectural design decisions.
This paper proposes a fast algorithm for additive white Gaussian noise level estimation from still digital images. The proposed algorithm uses a Laplacian operator to suppress the underlying image signal. In addition,...
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ISBN:
(纸本)9789532330922
This paper proposes a fast algorithm for additive white Gaussian noise level estimation from still digital images. The proposed algorithm uses a Laplacian operator to suppress the underlying image signal. In addition, the algorithm performs a non-overlapping block segmentation of images in conjunction with the local averaging to obtain the local noise level estimates. These local noise level estimates facilitate a variable block size image tessellation and adaptive estimation of homogenous image patches. Thus, the proposed algorithm can be described as a hybrid method as it adopts some principal characteristics of both filter-based and block-based methods. The performance of the proposed noise estimation algorithm is evaluated on a dataset of natural images. The results show that the proposed algorithm is able to provide a consistent performance across different image types and noise levels. In addition, it has been demonstrated that the adaptive nature of homogenous block estimation improves the computational efficiency of the algorithm.
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