Search results for: Discrete Breeding Swarm
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 820

Search results for: Discrete Breeding Swarm

310 Characterizations of Star-Shaped, L-Convex, and Convex Polygons

Authors: Thomas Shermer, Godfried T. Toussaint

Abstract:

A chord of a simple polygon P is a line segment [xy] that intersects the boundary of P only at both endpoints x and y. A chord of P is called an interior chord provided the interior of [xy] lies in the interior of P. P is weakly visible from [xy] if for every point v in P there exists a point w in [xy] such that [vw] lies in P. In this paper star-shaped, L-convex, and convex polygons are characterized in terms of weak visibility properties from internal chords and starshaped subsets of P. A new Krasnoselskii-type characterization of isothetic star-shaped polygons is also presented.

Keywords: Convex polygons, L-convex polygons, star-shaped polygons, chords, weak visibility, discrete and computational geometry

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309 Bernstein-Galerkin Approach for Perturbed Constant-Coefficient Differential Equations, One-Dimensional Analysis

Authors: Diego Garijo

Abstract:

A numerical approach for solving constant-coefficient differential equations whose solutions exhibit boundary layer structure is built by inserting Bernstein Partition of Unity into Galerkin variational weak form. Due to the reproduction capability of Bernstein basis, such implementation shows excellent accuracy at boundaries and is able to capture sharp gradients of the field variable by p-refinement using regular distributions of equi-spaced evaluation points. The approximation is subjected to convergence experimentation and a procedure to assemble the discrete equations without a background integration mesh is proposed.

Keywords: Bernstein polynomials, Galerkin, differential equation, boundary layer.

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308 Capacitor Placement in Radial Distribution System for Loss Reduction Using Artificial Bee Colony Algorithm

Authors: R. Srinivasa Rao

Abstract:

This paper presents a new method which applies an artificial bee colony algorithm (ABC) for capacitor placement in distribution systems with an objective of improving the voltage profile and reduction of power loss. The ABC algorithm is a new population based meta heuristic approach inspired by intelligent foraging behavior of honeybee swarm. The advantage of ABC algorithm is that it does not require external parameters such as cross over rate and mutation rate as in case of genetic algorithm and differential evolution and it is hard to determine these parameters in prior. The other advantage is that the global search ability in the algorithm is implemented by introducing neighborhood source production mechanism which is a similar to mutation process. To demonstrate the validity of the proposed algorithm, computer simulations are carried out on 69-bus system and compared the results with the other approach available in the literature. The proposed method has outperformed the other methods in terms of the quality of solution and computational efficiency.

Keywords: Distribution system, Capacitor Placement, Loss reduction, Artificial Bee Colony Algorithm.

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307 Design and Study of a DC/DC Converter for High Power, 14.4 V and 300 A for Automotive Applications

Authors: Julio Cesar Lopes de Oliveira, Carlos Henrique Gonc¸alves Treviso

Abstract:

The shortage of the automotive market in relation to options for sources of high power car audio systems, led to development of this work. Thus, we developed a source with stabilized voltage with 4320 W effective power. Designed to the voltage of 14.4 V and a choice of two currents: 30 A load option in battery banks and 300 A at full load. This source can also be considered as a source of general use dedicated commercial with a simple control circuit in analog form based on discrete components. The assembly of power circuit uses a methodology for higher power than the initially stipulated.

Keywords: DC-DC power converters, converters, power convertion, pulse width modulation converters.

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306 IPSO Based UPFC Robust Output Feedback Controllers for Damping of Low Frequency Oscillations

Authors: A. Safari, H. Shayeghi, H. A. Shayanfar

Abstract:

On the basis of the linearized Phillips-Herffron model of a single-machine power system, a novel method for designing unified power flow controller (UPFC) based output feedback controller is presented. The design problem of output feedback controller for UPFC is formulated as an optimization problem according to with the time domain-based objective function which is solved by iteration particle swarm optimization (IPSO) that has a strong ability to find the most optimistic results. To ensure the robustness of the proposed damping controller, the design process takes into account a wide range of operating conditions and system configurations. The simulation results prove the effectiveness and robustness of the proposed method in terms of a high performance power system. The simulation study shows that the designed controller by Iteration PSO performs better than Classical PSO in finding the solution.

Keywords: UPFC, IPSO, output feedback Controller.

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305 A Fuzzy Swarm Optimized Approach for Piece Selection in Bit Torrent Like Peer to Peer Network

Authors: M. Padmavathi, R. M. Suresh

Abstract:

Every machine plays roles of client and server simultaneously in a peer-to-peer (P2P) network. Though a P2P network has many advantages over traditional client-server models regarding efficiency and fault-tolerance, it also faces additional security threats. Users/IT administrators should be aware of risks from malicious code propagation, downloaded content legality, and P2P software’s vulnerabilities. Security and preventative measures are a must to protect networks from potential sensitive information leakage and security breaches. Bit Torrent is a popular and scalable P2P file distribution mechanism which successfully distributes large files quickly and efficiently without problems for origin server. Bit Torrent achieved excellent upload utilization according to measurement studies, but it also raised many questions as regards utilization in settings, than those measuring, fairness, and Bit Torrent’s mechanisms choice. This work proposed a block selection technique using Fuzzy ACO with optimal rules selected using ACO.

Keywords: Ant Colony Optimization (ACO), Bit Torrent, Download time, Peer-to-Peer (P2P) network, Performance.

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304 Exponential State Estimation for Neural Networks with Leakage, Discrete and Distributed Delays

Authors: Liyuan Wang, Shouming Zhong

Abstract:

In this paper, the design problem of state estimator for neural networks with the mixed time-varying delays are investigated by constructing appropriate Lyapunov-Krasovskii functionals and using some effective mathematical techniques. In order to derive several conditions to guarantee the estimation error systems to be globally exponential stable, we transform the considered systems into the neural-type time-delay systems. Then with a set of linear inequalities(LMIs), we can obtain the stable criteria. Finally, three numerical examples are given to show the effectiveness and less conservatism of the proposed criterion.

Keywords: State estimator, Neural networks, Globally exponential stability.

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303 Computational Intelligence Hybrid Learning Approach to Time Series Forecasting

Authors: Chunshien Li, Jhao-Wun Hu, Tai-Wei Chiang, Tsunghan Wu

Abstract:

Time series forecasting is an important and widely popular topic in the research of system modeling. This paper describes how to use the hybrid PSO-RLSE neuro-fuzzy learning approach to the problem of time series forecasting. The PSO algorithm is used to update the premise parameters of the proposed prediction system, and the RLSE is used to update the consequence parameters. Thanks to the hybrid learning (HL) approach for the neuro-fuzzy system, the prediction performance is excellent and the speed of learning convergence is much faster than other compared approaches. In the experiments, we use the well-known Mackey-Glass chaos time series. According to the experimental results, the prediction performance and accuracy in time series forecasting by the proposed approach is much better than other compared approaches, as shown in Table IV. Excellent prediction performance by the proposed approach has been observed.

Keywords: forecasting, hybrid learning (HL), Neuro-FuzzySystem (NFS), particle swarm optimization (PSO), recursiveleast-squares estimator (RLSE), time series

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302 A New Splitting H1-Galerkin Mixed Method for Pseudo-hyperbolic Equations

Authors: Yang Liu, Jinfeng Wang, Hong Li, Wei Gao, Siriguleng He

Abstract:

A new numerical scheme based on the H1-Galerkin mixed finite element method for a class of second-order pseudohyperbolic equations is constructed. The proposed procedures can be split into three independent differential sub-schemes and does not need to solve a coupled system of equations. Optimal error estimates are derived for both semidiscrete and fully discrete schemes for problems in one space dimension. And the proposed method dose not requires the LBB consistency condition. Finally, some numerical results are provided to illustrate the efficacy of our method.

Keywords: Pseudo-hyperbolic equations, splitting system, H1-Galerkin mixed method, error estimates.

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301 Real-Coded Genetic Algorithm for Robust Power System Stabilizer Design

Authors: Sidhartha Panda, C. Ardil

Abstract:

Power system stabilizers (PSS) are now routinely used in the industry to damp out power system oscillations. In this paper, real-coded genetic algorithm (RCGA) optimization technique is applied to design robust power system stabilizer for both singlemachine infinite-bus (SMIB) and multi-machine power system. The design problem of the proposed controller is formulated as an optimization problem and RCGA is employed to search for optimal controller parameters. By minimizing the time-domain based objective function, in which the deviation in the oscillatory rotor speed of the generator is involved; stability performance of the system is improved. The non-linear simulation results are presented under wide range of operating conditions; disturbances at different locations as well as for various fault clearing sequences to show the effectiveness and robustness of the proposed controller and their ability to provide efficient damping of low frequency oscillations.

Keywords: Particle swarm optimization, power system stabilizer, low frequency oscillations, power system stability.

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300 Texture Feature Extraction using Slant-Hadamard Transform

Authors: M. J. Nassiri, A. Vafaei, A. Monadjemi

Abstract:

Random and natural textures classification is still one of the biggest challenges in the field of image processing and pattern recognition. In this paper, texture feature extraction using Slant Hadamard Transform was studied and compared to other signal processing-based texture classification schemes. A parametric SHT was also introduced and employed for natural textures feature extraction. We showed that a subtly modified parametric SHT can outperform ordinary Walsh-Hadamard transform and discrete cosine transform. Experiments were carried out on a subset of Vistex random natural texture images using a kNN classifier.

Keywords: Texture Analysis, Slant Transform, Hadamard, DCT.

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299 Inferential Reasoning for Heterogeneous Multi-Agent Mission

Authors: Sagir M. Yusuf, Chris Baber

Abstract:

We describe issues bedeviling the coordination of heterogeneous (different sensors carrying agents) multi-agent missions such as belief conflict, situation reasoning, etc. We applied Bayesian and agents' presumptions inferential reasoning to solve the outlined issues with the heterogeneous multi-agent belief variation and situational-base reasoning. Bayesian Belief Network (BBN) was used in modeling the agents' belief conflict due to sensor variations. Simulation experiments were designed, and cases from agents’ missions were used in training the BBN using gradient descent and expectation-maximization algorithms. The output network is a well-trained BBN for making inferences for both agents and human experts. We claim that the Bayesian learning algorithm prediction capacity improves by the number of training data and argue that it enhances multi-agents robustness and solve agents’ sensor conflicts.

Keywords: Distributed constraint optimization problem, multi-agent system, multi-robot coordination, autonomous system, swarm intelligence.

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298 A New Time Discontinuous Expanded Mixed Element Method for Convection-dominated Diffusion Equation

Authors: Jinfeng Wang, Yuanhong Bi, Hong Li, Yang Liu, Meng Zhao

Abstract:

In this paper, a new time discontinuous expanded mixed finite element method is proposed and analyzed for two-order convection-dominated diffusion problem. The proofs of the stability of the proposed scheme and the uniqueness of the discrete solution are given. Moreover, the error estimates of the scalar unknown, its gradient and its flux in the L1( ¯ J,L2( )-norm are obtained.

Keywords: Convection-dominated diffusion equation, expanded mixed method, time discontinuous scheme, stability, error estimates.

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297 Increase of Error Detection Effectiveness in the Data Transmission Channels with Pulse-Amplitude Modulation

Authors: Akram A. Mustafa

Abstract:

In this paper an approaches for increasing the effectiveness of error detection in computer network channels with Pulse-Amplitude Modulation (PAM) has been proposed. Proposed approaches are based on consideration of special feature of errors, which are appearances in line with PAM. The first approach consists of CRC modification specifically for line with PAM. The second approach is base of weighted checksums using. The way for checksum components coding has been developed. It has been shown that proposed checksum modification ensure superior digital data control transformation reliability for channels with PAM in compare to CRC.

Keywords: Pulse-Amplitude Modulation, checksum, transmission, discrete.

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296 A High Bitrate Information Hiding Algorithm for Video in Video

Authors: Wang Shou-Dao, Xiao Chuang-Bai, Lin Yu

Abstract:

In high bitrate information hiding techniques, 1 bit is embedded within each 4 x 4 Discrete Cosine Transform (DCT) coefficient block by means of vector quantization, then the hidden bit can be effectively extracted in terminal end. In this paper high bitrate information hiding algorithms are summarized, and the scheme of video in video is implemented. Experimental result shows that the host video which is embedded numerous auxiliary information have little visually quality decline. Peak Signal to Noise Ratio (PSNR)Y of host video only degrades 0.22dB in average, while the hidden information has a high percentage of survives and keeps a high robustness in H.264/AVC compression, the average Bit Error Rate(BER) of hiding information is 0.015%.

Keywords: Information Hiding, Embed, Quantification, Extract

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295 Time-Delay Estimation Using Cross-ΨB-Energy Operator

Authors: Z. Saidi, A.O. Boudraa, J.C. Cexus, S. Bourennane

Abstract:

In this paper, a new time-delay estimation technique based on the cross IB-energy operator [5] is introduced. This quadratic energy detector measures how much a signal is present in another one. The location of the peak of the energy operator, corresponding to the maximum of interaction between the two signals, is the estimate of the delay. The method is a fully data-driven approach. The discrete version of the continuous-time form of the cross IBenergy operator, for its implementation, is presented. The effectiveness of the proposed method is demonstrated on real underwater acoustic signals arriving from targets and the results compared to the cross-correlation method.

Keywords: Teager-Kaiser energy operator, Cross-energyoperator, Time-Delay, Underwater acoustic signals.

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294 The Effect of Different Compression Schemes on Speech Signals

Authors: Jalal Karam, Raed Saad

Abstract:

This paper studies the effect of different compression constraints and schemes presented in a new and flexible paradigm to achieve high compression ratios and acceptable signal to noise ratios of Arabic speech signals. Compression parameters are computed for variable frame sizes of a level 5 to 7 Discrete Wavelet Transform (DWT) representation of the signals for different analyzing mother wavelet functions. Results are obtained and compared for Global threshold and level dependent threshold techniques. The results obtained also include comparisons with Signal to Noise Ratios, Peak Signal to Noise Ratios and Normalized Root Mean Square Error.

Keywords: Speech Compression, Wavelets.

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293 Using Neural Network for Execution of Programmed Pulse Width Modulation (PPWM) Method

Authors: M. Tarafdar Haque, A. Taheri

Abstract:

Application of neural networks in execution of programmed pulse width modulation (PPWM) of a voltage source inverter (VSI) is studied in this paper. Using the proposed method it is possible to cancel out the desired harmonics in output of VSI in addition to control the magnitude of fundamental harmonic, contineously. By checking the non-trained values and a performance index, the most appropriate neural network is proposed. It is shown that neural networks may solve the custom difficulties of practical utilization of PPWM such as large size of memory, complex digital circuits and controlling the magnitude of output voltage in a discrete manner.

Keywords: Neural Network, Inverter, PPWM.

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292 Wavelet Transform and Support Vector Machine Approach for Fault Location in Power Transmission Line

Authors: V. Malathi, N.S.Marimuthu

Abstract:

This paper presents a wavelet transform and Support Vector Machine (SVM) based algorithm for estimating fault location on transmission lines. The Discrete wavelet transform (DWT) is used for data pre-processing and this data are used for training and testing SVM. Five types of mother wavelet are used for signal processing to identify a suitable wavelet family that is more appropriate for use in estimating fault location. The results demonstrated the ability of SVM to generalize the situation from the provided patterns and to accurately estimate the location of faults with varying fault resistance.

Keywords: Fault location, support vector machine, supportvector regression, transmission lines, wavelet transform.

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291 DACS3: Embedding Individual Ant Behavior in Ant Colony System

Authors: Zulaiha Ali Othman, Helmi Md Rais, Abdul Razak Hamdan

Abstract:

Ants are fascinating creatures that demonstrate the ability to find food and bring it back to their nest. Their ability as a colony, to find paths to food sources has inspired the development of algorithms known as Ant Colony Systems (ACS). The principle of cooperation forms the backbone of such algorithms, commonly used to find solutions to problems such as the Traveling Salesman Problem (TSP). Ants communicate to each other through chemical substances called pheromones. Modeling individual ants- ability to manipulate this substance can help an ACS find the best solution. This paper introduces a Dynamic Ant Colony System with threelevel updates (DACS3) that enhance an existing ACS. Experiments were conducted to observe single ant behavior in a colony of Malaysian House Red Ants. Such behavior was incorporated into the DACS3 algorithm. We benchmark the performance of DACS3 versus DACS on TSP instances ranging from 14 to 100 cities. The result shows that the DACS3 algorithm can achieve shorter distance in most cases and also performs considerably faster than DACS.

Keywords: Dynamic Ant Colony System (DACS), TravelingSalesmen Problem (TSP), Optimization, Swarm Intelligent.

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290 Component Criticality Importance Measures in Thermal Power Plants Design

Authors: Smajo Bisanovic, Mensur Hajro, Mersiha Samardzic

Abstract:

This paper presents quantitative component criticality importance indices applicable for identifying and ranking critical components in the phase of thermal power plants design. Identifying critical components for power plant reliability provides one important input to decision-making and guidance throughout the development project. The study of components criticality importance indices to several characteristic structural schemes of conventional thermal power plant is presented and discussed.

Keywords: Component criticality importance measures, discrete event, reliability, thermal power plant.

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289 Solving 94-bit ECDLP with 70 Computers in Parallel

Authors: Shunsuke Miyoshi, Yasuyuki Nogami, Takuya Kusaka, Nariyoshi Yamai

Abstract:

Elliptic curve discrete logarithm problem(ECDLP) is one of problems on which the security of pairing-based cryptography is based. This paper considers Pollard’s rho method to evaluate the security of ECDLP on Barreto-Naehrig(BN) curve that is an efficient pairing-friendly curve. Some techniques are proposed to make the rho method efficient. Especially, the group structure on BN curve, distinguished point method, and Montgomery trick are well-known techniques. This paper applies these techniques and shows its optimization. According to the experimental results for which a large-scale parallel system with MySQL is applied, 94-bit ECDLP was solved about 28 hours by parallelizing 71 computers.

Keywords: Pollard’s rho method, BN curve, Montgomery multiplication.

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288 Effects of Introducing Similarity Measures into Artificial Bee Colony Approach for Optimization of Vehicle Routing Problem

Authors: P. Shunmugapriya, S. Kanmani, P. Jude Fredieric, U. Vignesh, J. Reman Justin, K. Vivek

Abstract:

Vehicle Routing Problem (VRP) is a complex combinatorial optimization problem and it is quite difficult to find an optimal solution consisting of a set of routes for vehicles whose total cost is minimum. Evolutionary and swarm intelligent (SI) algorithms play a vital role in solving optimization problems. While the SI algorithms perform search, the diversity between the solutions they exploit is very important. This is because of the need to avoid early convergence and to get an appropriate balance between the exploration and exploitation. Therefore, it is important to check how far the solutions are diverse. In this paper, we measure the similarity between solutions, which ABC exploits while optimizing VRP. The similar solutions found are discarded at the end of the iteration and only unique solutions are passed on to the next iteration. The bees of discarded solutions become scouts and they start searching for new solutions. This process is continued and results show that the solution is optimized at lesser number of iterations but with the overhead of computing similarity in all the iterations. The problem instance from Solomon benchmarked dataset has been used for evaluating the presented methodology.

Keywords: ABC algorithm, vehicle routing problem, optimization, Jaccard’s similarity measure.

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287 Innovative Methods of Improving Train Formation in Freight Transport

Authors: Jaroslav Masek, Juraj Camaj, Eva Nedeliakova

Abstract:

The paper is focused on the operational model for transport the single wagon consignments on railway network by using two different models of train formation. The paper gives an overview of possibilities of improving the quality of transport services. Paper deals with two models used in problematic of train formatting - time continuously and time discrete. By applying these models in practice, the transport company can guarantee a higher quality of service and expect increasing of transport performance. The models are also applicable into others transport networks. The models supplement a theoretical problem of train formation by new ways of looking to affecting the organization of wagon flows.

Keywords: Train formation, wagon flows, marshalling yard, railway technology.

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286 Maximum Norm Analysis of a Nonmatching Grids Method for Nonlinear Elliptic Boundary Value Problem −Δu = f(u)

Authors: Abida Harbi

Abstract:

We provide a maximum norm analysis of a finite element Schwarz alternating method for a nonlinear elliptic boundary value problem of the form -Δu = f(u), on two overlapping sub domains with non matching grids. We consider a domain which is the union of two overlapping sub domains where each sub domain has its own independently generated grid. The two meshes being mutually independent on the overlap region, a triangle belonging to one triangulation does not necessarily belong to the other one. Under a Lipschitz assumption on the nonlinearity, we establish, on each sub domain, an optimal L∞ error estimate between the discrete Schwarz sequence and the exact solution of the boundary value problem.

Keywords: Error estimates, Finite elements, Nonlinear PDEs, Schwarz method.

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285 DACS3:Embedding Individual Ant Behavior in Ant Colony System

Authors: Zulaiha Ali Othman, Helmi Md Rais, Abdul Razak Hamdan

Abstract:

Ants are fascinating creatures that demonstrate the ability to find food and bring it back to their nest. Their ability as a colony, to find paths to food sources has inspired the development of algorithms known as Ant Colony Systems (ACS). The principle of cooperation forms the backbone of such algorithms, commonly used to find solutions to problems such as the Traveling Salesman Problem (TSP). Ants communicate to each other through chemical substances called pheromones. Modeling individual ants- ability to manipulate this substance can help an ACS find the best solution. This paper introduces a Dynamic Ant Colony System with threelevel updates (DACS3) that enhance an existing ACS. Experiments were conducted to observe single ant behavior in a colony of Malaysian House Red Ants. Such behavior was incorporated into the DACS3 algorithm. We benchmark the performance of DACS3 versus DACS on TSP instances ranging from 14 to 100 cities. The result shows that the DACS3 algorithm can achieve shorter distance in most cases and also performs considerably faster than DACS.

Keywords: Dynamic Ant Colony System (DACS), Traveling Salesmen Problem (TSP), Optimization, Swarm Intelligent.

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284 Evolved Bat Algorithm Based Adaptive Fuzzy Sliding Mode Control with LMI Criterion

Authors: P.-W. Tsai, C.-Y. Chen, C.-W. Chen

Abstract:

In this paper, the stability analysis of a GA-Based adaptive fuzzy sliding model controller for a nonlinear system is discussed. First, a nonlinear plant is well-approximated and described with a reference model and a fuzzy model, both involving FLC rules. Then, FLC rules and the consequent parameter are decided on via an Evolved Bat Algorithm (EBA). After this, we guarantee a new tracking performance inequality for the control system. The tracking problem is characterized to solve an eigenvalue problem (EVP). Next, an adaptive fuzzy sliding model controller (AFSMC) is proposed to stabilize the system so as to achieve good control performance. Lyapunov’s direct method can be used to ensure the stability of the nonlinear system. It is shown that the stability analysis can reduce nonlinear systems into a linear matrix inequality (LMI) problem. Finally, a numerical simulation is provided to demonstrate the control methodology.

Keywords: Adaptive fuzzy sliding mode control, Lyapunov direct method, swarm intelligence, evolved bat algorithm.

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283 Blind Non-Minimum Phase Channel Identification Using 3rd and 4th Order Cumulants

Authors: S. Safi, A. Zeroual

Abstract:

In this paper we propose a family of algorithms based on 3rd and 4th order cumulants for blind single-input single-output (SISO) Non-Minimum Phase (NMP) Finite Impulse Response (FIR) channel estimation driven by non-Gaussian signal. The input signal represents the signal used in 10GBASE-T (or IEEE 802.3an-2006) as a Tomlinson-Harashima Precoded (THP) version of random Pulse-Amplitude Modulation with 16 discrete levels (PAM-16). The proposed algorithms are tested using three non-minimum phase channel for different Signal-to-Noise Ratios (SNR) and for different data input length. Numerical simulation results are presented to illustrate the performance of the proposed algorithms.

Keywords: Higher Order Cumulants, Channel identification, Ethernet communication.

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282 Passivity Analysis of Stochastic Neural Networks With Multiple Time Delays

Authors: Biao Qin, Jin Huang, Jiaojiao Ren, Wei Kang

Abstract:

This paper deals with the problem of passivity analysis for stochastic neural networks with leakage, discrete and distributed delays. By using delay partitioning technique, free weighting matrix method and stochastic analysis technique, several sufficient conditions for the passivity of the addressed neural networks are established in terms of linear matrix inequalities (LMIs), in which both the time-delay and its time derivative can be fully considered. A numerical example is given to show the usefulness and effectiveness of the obtained results.

Keywords: Passivity, Stochastic neural networks, Multiple time delays, Linear matrix inequalities (LMIs).

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281 ECG Analysis using Nature Inspired Algorithm

Authors: A.Sankara Subramanian, G.Gurusamy, G.Selvakumar, P.Gnanasekar, A.Nagappan

Abstract:

This paper presents an algorithm based on the wavelet decomposition, for feature extraction from the ECG signal and recognition of three types of Ventricular Arrhythmias using neural networks. A set of Discrete Wavelet Transform (DWT) coefficients, which contain the maximum information about the arrhythmias, is selected from the wavelet decomposition. After that a novel clustering algorithm based on nature inspired algorithm (Ant Colony Optimization) is developed for classifying arrhythmia types. The algorithm is applied on the ECG registrations from the MIT-BIH arrhythmia and malignant ventricular arrhythmia databases. We applied Daubechies 4 wavelet in our algorithm. The wavelet decomposition enabled us to perform the task efficiently and produced reliable results.

Keywords: Daubechies 4 Wavelet, ECG, Nature inspired algorithm, Ventricular Arrhythmias, Wavelet Decomposition.

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