Fuzzy fingerprint vault is proposed to provide a solution to user privacy and fingerprint template security problems. It binds fingerprint minutiae with a private key and scrambling it with a large amount of chaff min...
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In this study, a new type of trigonometric neural network is presented by adding frequency and phase to trigonometric activation functions. The proposed trigonometric neural network has more flexibility in comparison ...
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In this study, a new type of trigonometric neural network is presented by adding frequency and phase to trigonometric activation functions. The proposed trigonometric neural network has more flexibility in comparison with conventional trigonometric neural networks and even other types of neural networks. Due to the low convergence rate and high posibility of trapping in a local minimum of backpropagation algorithm, Extended Kalman Filter algorithm is used to train the neural network's parameters which they appear in a nonlinear form. The Simulation of the suggested neural network based on the prediction of Mackey-Glass time series and identification of a nonlinear dynamic ystem reveals the efficiency of the proposed network. To show the efficiency of this method, the results are compared with the results of the others.
In this paper, the distributed robust output regulation problem of linear multi-agent systems (MAS) is considered. The driving force from the active leaders or the environmental disturbances is formulated as an input ...
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In this paper, the distributed robust output regulation problem of linear multi-agent systems (MAS) is considered. The driving force from the active leaders or the environmental disturbances is formulated as an input of an exogenous system (or exosystem) of the considered multi-agent networks. A systematic distributed design approach is proposed to handle output regulation via dynamic output feedback with the help of canonical internal model (IM). With common solutions of regulator equations and Lyapunov functions, the distributed robust output regulation with switching interconnection topology is designed to achieve collective aims.
Bayesian network is an important diagram structure. It is used in many domains such as DNA analysis, macro economic prediction, finance risk analysis and market forecast. We propose a novel Bayesian network learning m...
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Chapter 1 briefly introduces the problem formations and the organization of the book. In particular, given a feasible set of switching signals, the concepts of stability and stabilizability are introduced, and the rel...
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This paper deals with the estimation of a gramian-based interaction measure from logged process data, and thereby removing the need of creating parametric models prior to the selection of the significant input-output ...
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ISBN:
(纸本)9781612848006
This paper deals with the estimation of a gramian-based interaction measure from logged process data, and thereby removing the need of creating parametric models prior to the selection of the significant input-output interconnections. Moreover, the resulting confidence regions of the estimates can be used to perform a robust control structure selection. The considered interaction measure is the Participation Matrix. Based on previous results, a new unbiased statistic is proposed, and confidence bounds for the estimate are derived. Examples and a case study are used to illustrate how the method can be applied.
The Residue Number System (RNS) is a non weighted system. It supports parallel, high speed, low power and secure arithmetic. Detecting overflow in RNS systems is very important, because if overflow is not detected pro...
The Residue Number System (RNS) is a non weighted system. It supports parallel, high speed, low power and secure arithmetic. Detecting overflow in RNS systems is very important, because if overflow is not detected properly, an incorrect result may be considered as a correct answer. The previously proposed methods or algorithms for detecting overflow need to residue comparison or complete convert of numbers from RNS to binary. We propose a new and fast overflow detection approach for moduli set {2n-1, 2n, 2n+1}, which it is different from previous methods. Our technique implements RNS overflow detection much faster applying a few more hardware than previous methods.
In this paper, a hybrid control approach for low temperature combustion engines is presented. The identification as well as the controller design are demonstrated. In order to identify piecewise affine models, we prop...
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ISBN:
(纸本)9781612848006
In this paper, a hybrid control approach for low temperature combustion engines is presented. The identification as well as the controller design are demonstrated. In order to identify piecewise affine models, we propose to use correlation clustering algorithms, which are developed and used in the field of data mining. We outline the identification of the low temperature combustion engine from measurement data based on correlation clustering. The output of the identified model reproduces the measurement data of the engine very well. Based on this piecewise affine model of the process, a hybrid model predictive controller is considered. It can be shown that the hybrid contoller is able to produce better control results than a model predictive controller using a single linear model. The main advantage is that the hybrid controller is able to manage the system characteristics of different operating points for each prediction step.
Achieving high performance optimization algorithms for embedded applications can be very challenging, particularly when several requirements such as high accuracy computations, short elapsed time, area cost, low power...
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Achieving high performance optimization algorithms for embedded applications can be very challenging, particularly when several requirements such as high accuracy computations, short elapsed time, area cost, low power consumption and portability must be accomplished. This paper proposes a hardware implementation of the Particle Swarm Optimization algorithm with passive congregation (HPPSOpc), which was developed using several floating-point arithmetic libraries. The passive congregation is a biological behavior which allows the swarm to preserve its integrity, balancing between global and local search. The HPPSOpc architecture was implemented on a Virtex5 FPGA device and validated using two multimodal benchmark problems. Synthesis, simulation and execution time results demonstrates that the passive congregation approach is a low cost solution for solving embedded optimization problems with a high performance.
A Taguchi-sliding-based differential evolution algorithm (TSBDEA) is proposed in this study to solve the problem of optimally approximating linear systems. The TSBDEA is an approach of combining the differential evolu...
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