In the last few years great attention has been concentrated on the consensus algorithm in a network of agents. A consensus problem in which the agreement value is a distributed estimation of some non-constant quantity...
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In the last few years great attention has been concentrated on the consensus algorithm in a network of agents. A consensus problem in which the agreement value is a distributed estimation of some non-constant quantity of interest is referred to as a dynamic consensus. In practical applications an effective network architecture to support sensing and communication between agents is based on a Wireless Sensor Network (WSN). This paper deals with the design of a fast dynamic consensus algorithm when it is implemented over the WSN. A sufficient stability condition of the dynamic consensus algorithm in the presence of heterogeneous time delays affecting communication through the multi hops of the WSN is introduced and used for consensus algorithm gain design. Moreover, the algorithm implementation by the standard AODV routing protocol is discussed and the best parameter setting to reduce the effect of packet collision phenomena on the performance of the consensus algorithm is indicated. Several trade-offs between network parameter setting, sensor node technology selection and application performance have to be taken into account by the designer in the implementation of the dynamic consensus algorithm. A representative simulation based design procedure is presented to validate through realistic simulation experiments the proposed design approach. (C) 2012 Elsevier Ltd. All rights reserved.
Solar energy is renewable energy which can be used in the drying of agricultural and sideline products. The lower computer measurement and control subsystem is designed and the improved binary table lookup algorithm i...
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ISBN:
(纸本)9781479951994
Solar energy is renewable energy which can be used in the drying of agricultural and sideline products. The lower computer measurement and control subsystem is designed and the improved binary table lookup algorithm is designed to realize the tank water temperature detection. The main program flow is demonstrated, furthermore, the host computer monitoring subsystem is constructed, in which the system database and communication mechanism are designed, and the algorithm design of host computer communication module is demonstrated. The man-machine interface is quite friendly for the user. Using this solar dring system, some drying experiments for longan and red pepper are done. Experiments show that the drying system can run reliably, therefore, software design of the intelligent solar drying system is effective.
With the rapid proliferation of RFID technologies, RFID has been introduced to the applications like safety inspection and warehouse management. Conventionally a number of deployment rules are specified for these appl...
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With the rapid proliferation of RFID technologies, RFID has been introduced to the applications like safety inspection and warehouse management. Conventionally a number of deployment rules are specified for these applications. This paper studies a practically important problem of rule checking over RFID tags, i.e., checking whether the specified rules are satisfied according to the RFID tags within the monitoring area. This rule checking function may need to be executed frequently over a large number of tags and therefore should be made efficient in terms of execution time. Aiming to achieve time efficiency, we respectively propose two protocols, CRCP and ECRCP. CRCP works based on collision detection, while ECRCP combines the collision detection and the logical features of the rules. Simulation results indicate that our protocols achieve much better performance than other solutions in terms of time efficiency.
Estimation of a binary source using multiple observers, a variant of the so called Chief Executive Officer (CEO) problem, is considered. A low-complexity Distributed Joint Source Channel Coding (D-JSCC) based on the P...
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Estimation of a binary source using multiple observers, a variant of the so called Chief Executive Officer (CEO) problem, is considered. A low-complexity Distributed Joint Source Channel Coding (D-JSCC) based on the Parallel Concatenated Convolutional Codes (PCCC) is implemented in a cluster of sensors in a distributed fashion. Convergence of the iterative decoder is analyzed by utilizing EXtrinsic Information Transfer (EXIT) chart technique to determine the convergence region in terms of the sensors observation accuracy and channel SNR, where the iterative decoder outperforms the non-iterative one. This leads to design of a bi-modal decoder that adaptively switches between the iterative and non-iterative modes in order to avoid inefficient iterative information exchange without compromising the resulting Bit Error Rate (BER). This adaptive decoding algorithm saves the computational power and decoding time by a factor of about 10 by avoiding unnecessary iterations.
Distance adaptive spectrum allocation exploits the tradeoff between spectrum width and reach to improve resource utilization by tailoring the modulation format to the level of impairments along the path. We first show...
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ISBN:
(纸本)9781479959532
Distance adaptive spectrum allocation exploits the tradeoff between spectrum width and reach to improve resource utilization by tailoring the modulation format to the level of impairments along the path. We first show that the distance-adaptive routing and spectrum assignment (DA-RSA) problem in mesh networks is a special case of a multiprocessor scheduling problem. We then develop a suite of efficient and effective DA-RSA algorithms that build upon list scheduling concepts. Our work explores the tradeoffs involved in DA-RSA algorithm design, and opens up new research directions that may leverage the vast literature in scheduling theory.
Heuristic based algorithms are typically constructed following an iterative process in which the designer gradually introduces or modifies components or strategies whose performance is then tested by empirical evaluat...
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Heuristic based algorithms are typically constructed following an iterative process in which the designer gradually introduces or modifies components or strategies whose performance is then tested by empirical evaluation on one or more sets of benchmark problems. This process often starts with some generic or broadly applicable problem solving method (e.g., metaheuristics, backtracking search), a new algorithmic idea or even an algorithm suggested by theoretical considerations. Then, through an iterative process, various combinations of components, methods and strategies are implemented/improved and tested. Even experienced designers often have to spend substantial amounts of time exploring and experimenting with different alternatives before obtaining an effective algorithm for a given problem. In this work, we are interested in assisting the designer in this task. Considering that components, methods and strategies are generally associated with parameters and parameter values, we propose a method able to detect, through a fine-tuning process, ineffective and redundant components/strategies of an algorithm. The approach is a model-free method and applies simple consistency techniques in order to discard values from the domain of the parameters. We validate our approach with two algorithms for solving SAT and MIP problems. (C) 2014 Elsevier B.V. All rights reserved.
Here, a cascade-like hybrid tomography technology is proposed to solve the crosswell seismic inversion problem. This new method combines several widely used tomography technologies, implemented in a sequence starting ...
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Here, a cascade-like hybrid tomography technology is proposed to solve the crosswell seismic inversion problem. This new method combines several widely used tomography technologies, implemented in a sequence starting with the Radon-transform-based back-projection method, then the Linear Iterative Reconstruction method, next the nonlinear Gradient-based Eikonal Equation Tomography method, and finally full waveform inversion.
This work focuses on modelling and fault tolerant algorithm design of a damaged near space vehicle. A novel radial basis function (RBF) neural network backstepping fault-tolerant control methodology is developed for a...
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This work focuses on modelling and fault tolerant algorithm design of a damaged near space vehicle. A novel radial basis function (RBF) neural network backstepping fault-tolerant control methodology is developed for attitude control system with damage, which can make system stable and accurately track the desired signals in the presence of vertical tail loss. First, the changing aerodynamic parameters caused by vertical tail loss are used to model damaged attitude dynamics. Second, in view of the established damaged model, a nominal backstepping controller is designed. Then a RBF neural network technology is designed to update the related parameters, which can compensate effects caused by damage and make the system still stable and track the desired signals. Finally, simulation results are provided to show the effectiveness of the proposed RBF neural network backstepping fault-tolerant control scheme.
In order to enhance the optimization ability of the quantum evolutionary algorithms, a new quantum-behaved evolutionary algorithm is proposed. In this algorithm, the search mechanism is established based on the Bloch ...
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In order to enhance the optimization ability of the quantum evolutionary algorithms, a new quantum-behaved evolutionary algorithm is proposed. In this algorithm, the search mechanism is established based on the Bloch sphere. First, the individuals are expressed by qubits described on the Bloch sphere, then the rotation axis is established by Pauli matrixes, and the evolution search is realized by rotating qubits on the Bloch sphere about the rotating axis. In order to avoid premature convergence, the mutation of individuals is achieved by the Hadamard gates. Such rotation can make the current qubit approximate the target qubit along with the great circle on the Bloch sphere, which can accelerate optimization process. Taking the function extreme value optimization as an example, the experimental results show that the proposed algorithm is obviously superior to other similar algorithms. (C) 2013 Elsevier B. V. All rights reserved.
In this paper, we propose some improvements that enhance the optimization ability of quantum-behaved particle swarm optimization algorithms. First, we propose an encoding approach based on qubits described on the Bloc...
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In this paper, we propose some improvements that enhance the optimization ability of quantum-behaved particle swarm optimization algorithms. First, we propose an encoding approach based on qubits described on the Bloch sphere. In our approach, each particle contains three groups of Bloch coordinates of qubits, and all three groups of coordinates are regarded as approximate solutions describing the optimization result. Our approach updates the particles using the rotation of qubits about an axis on the Bloch sphere. This updating approach can simultaneously adjust two parameters of qubits, and can automatically achieve the best matching of two adjustments. To avoid premature convergence, the mutation is performed with Hadamard gates. The optimization process is performed in the n-dimensional hypercube space [-1,1] (n) , so the proposed approach can be easily adapted to a variety of optimization problems. The experimental results show that the proposed algorithm is superior to the original one in optimization ability.
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