Search results for: Linear complementarity problem

Authors: M. B. Meenavathi, K. Rajesh

Abstract:

Color image segmentation plays an important role in computer vision and image processing areas. In this paper, the features of Volterra filter are utilized for color image segmentation. The discrete Volterra filter exhibits both linear and nonlinear characteristics. The linear part smoothes the image features in uniform gray zones and is used for getting a gross representation of objects of interest. The nonlinear term compensates for the blurring due to the linear term and preserves the edges which are mainly used to distinguish the various objects. The truncated quadratic Volterra filters are mainly used for edge preserving along with Gaussian noise cancellation. In our approach, the segmentation is based on K-means clustering algorithm in HSI space. Both the hue and the intensity components are fully utilized. For hue clustering, the special cyclic property of the hue component is taken into consideration. The experimental results show that the proposed technique segments the color image while preserving significant features and removing noise effects.

Keywords: Color image segmentation, HSI space, K–means clustering, Volterra filter.

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Authors: Yongxin Yuan, Jiashang Jiang

Abstract:

In this paper the gradient based iterative algorithm is presented to solve the linear matrix equation AXB +CXTD = E, where X is unknown matrix, A,B,C,D,E are the given constant matrices. It is proved that if the equation has a solution, then the unique minimum norm solution can be obtained by choosing a special kind of initial matrices. Two numerical examples show that the introduced iterative algorithm is quite efficient.

Keywords: matrix equation, iterative algorithm, parameter estimation, minimum norm solution.

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Authors: Elena Ezhova, Vadim Mottl, Olga Krasotkina

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The problem of estimating time-varying regression is inevitably concerned with the necessity to choose the appropriate level of model volatility - ranging from the full stationarity of instant regression models to their absolute independence of each other. In the stationary case the number of regression coefficients to be estimated equals that of regressors, whereas the absence of any smoothness assumptions augments the dimension of the unknown vector by the factor of the time-series length. The Akaike Information Criterion is a commonly adopted means of adjusting a model to the given data set within a succession of nested parametric model classes, but its crucial restriction is that the classes are rigidly defined by the growing integer-valued dimension of the unknown vector. To make the Kullback information maximization principle underlying the classical AIC applicable to the problem of time-varying regression estimation, we extend it onto a wider class of data models in which the dimension of the parameter is fixed, but the freedom of its values is softly constrained by a family of continuously nested a priori probability distributions.

Keywords: Time varying regression, time-volatility of regression coefficients, Akaike Information Criterion (AIC), Kullback information maximization principle.

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Authors: Joselito Medina Marin, Norberto Hernández Romero, Juan Carlos Seck Tuoh Mora, Erick S. Martinez Gomez

Abstract:

The Flow Shop Scheduling Problem (FSSP) is a typical problem that is faced by production planning managers in Flexible Manufacturing Systems (FMS). This problem consists in finding the optimal scheduling to carry out a set of jobs, which are processed in a set of machines or shared resources. Moreover, all the jobs are processed in the same machine sequence. As in all the scheduling problems, the makespan can be obtained by drawing the Gantt chart according to the operations order, among other alternatives. On this way, an FMS presenting the FSSP can be modeled by Petri nets (PNs), which are a powerful tool that has been used to model and analyze discrete event systems. Then, the makespan can be obtained by simulating the PN through the token game animation and incidence matrix. In this work, we present an adaptive PN to obtain the makespan of FSSP by applying PN analytical tools.

Keywords: Flow-shop scheduling problem, makespan, Petri nets, state equation.

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Authors: Kamil Aida-zade, C. Ardil

Abstract:

In this paper, some problem formulations of dynamic object parameters recovery described by non-autonomous system of ordinary differential equations with multipoint unshared edge conditions are investigated. Depending on the number of additional conditions the problem is reduced to an algebraic equations system or to a problem of quadratic programming. With this purpose the paper offers a new scheme of the edge conditions transfer method called by conditions shift. The method permits to get rid from differential links and multipoint unshared initially-edge conditions. The advantage of the proposed approach is concluded by capabilities of reduction of a parametric identification problem to essential simple problems of the solution of an algebraic system or quadratic programming.

Keywords: dynamic objects, ordinary differential equations, multipoint unshared edge conditions, quadratic programming, conditions shift

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Authors: Michal Natora, Felix Franke, Klaus Obermayer

Abstract:

Linear convolutive filters are fast in calculation and in application, and thus, often used for real-time processing of continuous data streams. In the case of transient signals, a filter has not only to detect the presence of a specific waveform, but to estimate its arrival time as well. In this study, a measure is presented which indicates the performance of detectors in achieving both of these tasks simultaneously. Furthermore, a new sub-class of linear filters within the class of filters which minimize the quadratic response is proposed. The proposed filters are more flexible than the existing ones, like the adaptive matched filter or the minimum power distortionless response beamformer, and prove to be superior with respect to that measure in certain settings. Simulations of a real-time scenario confirm the advantage of these filters as well as the usefulness of the performance measure.

Keywords: Adaptive matched filter, minimum variance distortionless response, beam forming, Capon beam former, linear filters, performance measure.

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Authors: K. -H. Yang

Abstract:

Supplier selection problem is one of the important issues of supply chain problems. Two categories of methodologies include qualitative and quantitative approaches which can be applied to supplier selection problems. However, due to the complexities of the problem and lacking of reliable and quantitative data, qualitative approaches are more than quantitative approaches. This study considers operational cost and supplier’s reliability factor and solves the problem by using a quantitative approach. A mixed integer programming model is the primary analytic tool. Analyses of different scenarios with variable cost and reliability structures show that the effectiveness of this approach to the supplier selection problem.

Keywords: Mixed integer programming, quantitative approach, supplier’s reliability, supplier selection.

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Authors: Zhouji Chen

Abstract:

In this paper, the modified Gauss-Seidel method with the new preconditioner for solving the linear system Ax = b, where A is a nonsingular M-matrix with unit diagonal, is considered. The convergence property and the comparison theorems of the proposed method are established. Two examples are given to show the efficiency and effectiveness of the modified Gauss-Seidel method with the presented new preconditioner.

Keywords: Preconditioned linear system, M-matrix, Convergence, Comparison theorem.

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Authors: Flur R. Ismagilov, Vyacheslav E. Vavilov, Denis V. Gusakov

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This paper is devoted to solve the problem of increasing the electrification of aircraft engines by installing a synchronous generator at high pressure shaft. Technical solution of this problem by various research centers is discussed. A design solution of the problem was proposed. To evaluate the effectiveness of the proposed cooling system, thermal analysis was carried out in ANSYS software.

Keywords: Flur R. Ismagilov, Vyacheslav E. Vavilov, Denis V. Gusakov

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Authors: Miaomiao Yang, Shouming Zhong

Abstract:

This paper studies the problem of exponential stability analysis for recurrent neural networks with time-varying delay.By establishing a suitable augmented LyapunovCKrasovskii function and a novel sufficient condition is obtained to guarantee the exponential stability of the considered system.In order to get a less conservative results of the condition,zero equalities and reciprocally convex approach are employed. The several exponential stability criterion proposed in this paper is simpler and effective. A numerical example is provided to demonstrate the feasibility and effectiveness of our results.

Keywords: Exponential stability , Neural networks, Linear matrix inequality, Lyapunov-Krasovskii, Time-varying.

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Authors: Atman Jbari, Abdellah Adib, Driss Aboutajdine

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This paper addresses the problem of blind source separation (BSS). To recover original signals, from linear instantaneous mixtures, we propose a new contrast function based on the use of a double referenced system. Our approach assumes statistical independence sources. The reference vectors will be incrusted in the cumulant to evaluate the independence. The estimation of the separating matrix will be performed in two steps: whitening observations and joint diagonalization of a set of referenced cumulant matrices. Computer simulations are presented to demonstrate the effectiveness of the suggested approach.

Keywords: Blind source separation, Referenced Cumulant, Contrast, Joint Diagonalization.

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Authors: Hong Li, Shou-Ming Zhong, Hou-Biao Li

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In this paper, we mainly study the stability of linear and interval linear fractional systems with time delay. By applying the characteristic equations, a necessary and sufficient stability condition is obtained firstly, and then some sufficient conditions are deserved. In addition, according to the equivalent relationship of fractional order systems with order 0 < α ≤ 1 and with order 1 ≤ β < 2, one may get more relevant theorems. Finally, two examples are provided to demonstrate the effectiveness of our results.

Keywords: Fractional order systems, Time delay, Characteristic equation.

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Authors: Y. Abdelrazig

Abstract:

Evolutionary optimization methods such as genetic algorithms have been used extensively for the construction site layout problem. More recently, ant colony optimization algorithms, which are evolutionary methods based on the foraging behavior of ants, have been successfully applied to benchmark combinatorial optimization problems. This paper proposes a formulation of the site layout problem in terms of a sequencing problem that is suitable for solution using an ant colony optimization algorithm. In the construction industry, site layout is a very important planning problem. The objective of site layout is to position temporary facilities both geographically and at the correct time such that the construction work can be performed satisfactorily with minimal costs and improved safety and working environment. During the last decade, evolutionary methods such as genetic algorithms have been used extensively for the construction site layout problem. This paper proposes an ant colony optimization model for construction site layout. A simple case study for a highway project is utilized to illustrate the application of the model.

Keywords: Construction site layout, optimization, ant colony.

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Authors: Zixin Liu, Shu Lü, Shouming Zhong, Mao Ye

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In this paper, the robust exponential stability problem of uncertain discrete-time recurrent neural networks with timevarying delay is investigated. By constructing a new augmented Lyapunov-Krasovskii function, some new improved stability criteria are obtained in forms of linear matrix inequality (LMI). Compared with some recent results in literature, the conservatism of the new criteria is reduced notably. Two numerical examples are provided to demonstrate the less conservatism and effectiveness of the proposed results.

Keywords: Robust exponential stability, delay-dependent stability, discrete-time neutral networks, time-varying delays.

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Authors: Michal Polanský, C. Ardil

Abstract:

This paper shows a new method for design of fuzzy observers for Takagi-Sugeno systems. The method is based on Linear matrix inequalities (LMIs) and it allows to insert H constraint into the design procedure. The speed of estimation can tuned be specification of a decay rate of the observer closed loop system. We discuss here also the influence of parametric uncertainties at the output control system stability.

Keywords: H norm, Linear Matrix Inequalities, Observers, Takagi-Sugeno Systems, Parallel Distributed Compensation

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Authors: Sidhartha Panda, N. P. Padhy

Abstract:

This paper investigates the application of Particle Swarm Optimization (PSO) technique for coordinated design of a Power System Stabilizer (PSS) and a Thyristor Controlled Series Compensator (TCSC)-based controller to enhance the power system stability. The design problem of PSS and TCSC-based controllers is formulated as a time domain based optimization problem. PSO algorithm 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. To compare the capability of PSS and TCSC-based controller, both are designed independently first and then in a coordinated manner for individual and coordinated application. The proposed controllers are tested on a weakly connected power system. The eigenvalue analysis and non-linear simulation results are presented to show the effectiveness of the coordinated design approach over individual design. The simulation results show that the proposed controllers are effective in damping low frequency oscillations resulting from various small disturbances like change in mechanical power input and reference voltage setting.

Keywords: Particle swarm optimization, Phillips-Heffron model, power system stability, PSS, TCSC.

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Authors: Qingqing Wang, Baocheng Chen, Shouming Zhong

Abstract:

This paper deals with the problem of stability of neural networks with leakage, discrete and distributed delays. A new Lyapunov functional which contains some new double integral terms are introduced. By using appropriate model transformation that shifts the considered systems into the neutral-type time-delay system, and by making use of some inequality techniques, delay-dependent criteria are developed to guarantee the stability of the considered system. Finally, numerical examples are provided to illustrate the usefulness of the proposed main results.

Keywords: Neural networks, Stability, Time-varying delays, Linear matrix inequality.

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Authors: A. Shirzadeh Chaleshtari, Sh. Shadrokh

Abstract:

Renewable and non-renewable resource constraints have been vast studied in theoretical fields of project scheduling problems. However, although cumulative resources are widespread in practical cases, the literature on project scheduling problems subject to these resources is scant. So in order to study this type of resources more, in this paper we use the framework of a resource constrained project scheduling problem (RCPSP) with finish-start precedence relations between activities and subject to the cumulative resources in addition to the renewable resources. We develop a branch and bound algorithm for this problem customizing precedence tree algorithm of RCPSP. We perform extensive experimental analysis on the algorithm to check its effectiveness and performance for solving different instances of the problem in question.

Keywords: Resource constrained project scheduling problem, cumulative resources, branch and bound algorithm, precedence tree.

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Authors: G. Parmar, R. Prasad, S. Mukherjee

Abstract:

The authors present an algorithm for order reduction of linear dynamic systems using the combined advantages of stability equation method and the error minimization by Genetic algorithm. The denominator of the reduced order model is obtained by the stability equation method and the numerator terms of the lower order transfer function are determined by minimizing the integral square error between the transient responses of original and reduced order models using Genetic algorithm. The reduction procedure is simple and computer oriented. It is shown that the algorithm has several advantages, e.g. the reduced order models retain the steady-state value and stability of the original system. The proposed algorithm has also been extended for the order reduction of linear multivariable systems. Two numerical examples are solved to illustrate the superiority of the algorithm over some existing ones including one example of multivariable system.

Keywords: Genetic algorithm, Integral square error, Orderreduction, Stability equation method.

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Authors: Hassan Berbia, Faissal Elbouanani, Rahal Romadi, Mostafa Belkasmi

Abstract:

This paper introduces two decoders for binary linear codes based on Metaheuristics. The first one uses a genetic algorithm and the second is based on a combination genetic algorithm with a feed forward neural network. The decoder based on the genetic algorithms (DAG) applied to BCH and convolutional codes give good performances compared to Chase-2 and Viterbi algorithm respectively and reach the performances of the OSD-3 for some Residue Quadratic (RQ) codes. This algorithm is less complex for linear block codes of large block length; furthermore their performances can be improved by tuning the decoder-s parameters, in particular the number of individuals by population and the number of generations. In the second algorithm, the search space, in contrast to DAG which was limited to the code word space, now covers the whole binary vector space. It tries to elude a great number of coding operations by using a neural network. This reduces greatly the complexity of the decoder while maintaining comparable performances.

Keywords: Block code, decoding, methaheuristic, genetic algorithm, neural network

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Authors: Bin Cai, Shilong Wang, Haibo Hu

Abstract:

The job shop scheduling problem (JSSP) is well known as one of the most difficult combinatorial optimization problems. This paper presents a hybrid genetic algorithm for the JSSP with the objective of minimizing makespan. The efficiency of the genetic algorithm is enhanced by integrating it with a local search method. The chromosome representation of the problem is based on operations. Schedules are constructed using a procedure that generates full active schedules. In each generation, a local search heuristic based on Nowicki and Smutnicki-s neighborhood is applied to improve the solutions. The approach is tested on a set of standard instances taken from the literature and compared with other approaches. The computation results validate the effectiveness of the proposed algorithm.

Keywords: Genetic algorithm, Job shop scheduling problem, Local search, Meta-heuristic algorithm

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Authors: H. Mahboubi, B. Moshiri, A. Khaki Seddigh

Abstract:

In the past decade, because of wide applications of hybrid systems, many researchers have considered modeling and control of these systems. Since switching systems constitute an important class of hybrid systems, in this paper a method for optimal control of linear switching systems is described. The method is also applied on the two-tank system which is a much appropriate system to analyze different modeling and control techniques of hybrid systems. Simulation results show that, in this method, the goals of control and also problem constraints can be satisfied by an appropriate selection of cost function.

Keywords: Hybrid systems, optimal control, switched systems, two-tank system

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Authors: Sayyed R Mousavi

Abstract:

The Far From Most Strings Problem (FFMSP) is to obtain a string which is far from as many as possible of a given set of strings. All the input and the output strings are of the same length, and two strings are said to be far if their hamming distance is greater than or equal to a given positive integer. FFMSP belongs to the class of sequences consensus problems which have applications in molecular biology. The problem is NP-hard; it does not admit a constant-ratio approximation either, unless P = NP. Therefore, in addition to exact and approximate algorithms, (meta)heuristic algorithms have been proposed for the problem in recent years. On the other hand, in the recent years, hybrid algorithms have been proposed and successfully used for many hard problems in a variety of domains. In this paper, a new metaheuristic algorithm, called Constructive Beam and Local Search (CBLS), is investigated for the problem, which is a hybridization of constructive beam search and local search algorithms. More specifically, the proposed algorithm consists of two phases, the first phase is to obtain several candidate solutions via the constructive beam search and the second phase is to apply local search to the candidate solutions obtained by the first phase. The best solution found is returned as the final solution to the problem. The proposed algorithm is also similar to memetic algorithms in the sense that both use local search to further improve individual solutions. The CBLS algorithm is compared with the most recent published algorithm for the problem, GRASP, with significantly positive results; the improvement is by order of magnitudes in most cases.

Keywords: Bioinformatics, Far From Most Strings Problem, Hybrid metaheuristics, Matheuristics, Sequences consensus problems.

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Authors: Qingqing Wang, Baocheng Chen, Shouming Zhong

Abstract:

In this paper, the problem of stability criteria for Markovian jumping BAM neural networks with leakage and discrete delays has been investigated. Some new sufficient condition are derived based on a novel Lyapunov-Krasovskii functional approach. These new criteria based on delay partitioning idea are proved to be less conservative because free-weighting matrices method and a convex optimization approach are considered. Finally, one numerical example is given to illustrate the the usefulness and feasibility of the proposed main results.

Keywords: Stability, Markovian jumping neural networks, Timevarying delays, Linear matrix inequality.

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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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Authors: Adam Roman

Abstract:

Finding synchronizing sequences for the finite automata is a very important problem in many practical applications (part orienters in industry, reset problem in biocomputing theory, network issues etc). Problem of finding the shortest synchronizing sequence is NP-hard, so polynomial algorithms probably can work only as heuristic ones. In this paper we propose two versions of polynomial algorithms which work better than well-known Eppstein-s Greedy and Cycle algorithms.

Keywords: Synchronizing words, reset sequences, Černý Conjecture

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Authors: N. B. Fedosenko, A.A Iatcenko, S.A. Levanov

Abstract:

The paper shows some ability to manage two-phase flows arising from the use of unsteady effects. In one case, we consider the condition of fragmentation of the interface between the two components leads to the intensification of mixing. The problem is solved when the temporal and linear scale are small for the appearance of the developed mixing layer. Showing that exist such conditions for unsteady flow velocity at the surface of the channel, which will lead to the creation and fragmentation of vortices at Re numbers of order unity. Also showing that the Re is not a criterion of similarity for this type of flows, but we can introduce a criterion that depends on both the Re, and the frequency splitting of the vortices. It turned out that feature of this situation is that streamlines behave stable, and if we analyze the behavior of the interface between the components it satisfies all the properties of unstable flows. The other problem we consider the behavior of solid impurities in the extensive system of channels. Simulated unsteady periodic flow modeled breaths. Consider the behavior of the particles along the trajectories. It is shown that, depending on the mass and diameter of the particles, they can be collected in a caustic on the channel walls, stop in a certain place or fly back. Of interest is the distribution of particle velocity in frequency. It turned out that by choosing a behavior of the velocity field of the carrier gas can affect the trajectory of individual particles including force them to fly back.

Keywords: Two-phase, mixing, separating, flow control

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Authors: Houda Bdiri Gabbouj, Néjib Hassen, Kamel Besbes

Abstract:

This paper presents a low-voltage low-power differential linear transconductor with near rail-to-rail input swing. Based on the current-mirror OTA topology, the proposed transconductor combines the Flipped Voltage Follower (FVF) technique to linearize the transconductor behavior that leads to class- AB linear operation and the virtual transistor technique to lower the effective threshold voltages of the transistors which offers an advantage in terms of low supply requirement. Design of the OTA has been discussed. It operates at supply voltages of about ±0.8V. Simulation results for 0.18μm TSMC CMOS technology show a good input range of 1Vpp with a high DC gain of 81.53dB and a total harmonic distortion of -40dB at 1MHz for an input of 1Vpp. The main aim of this paper is to present and compare new OTA design with high transconductance, which has a potential to be used in low voltage applications.

Keywords: Amplifier class AB, current mirror, flipped voltage follower, low voltage.

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Authors: Hossein Nourkhiz Mahjoub, Mohsen Shiva

Abstract:

Wireless Mesh Networking is a promising proposal for broadband data transmission in a large area with low cost and acceptable QoS. These features- trade offs in WMNs is a hot research field nowadays. In this paper a mathematical optimization framework has been developed to maximize throughput according to upper bound delay constraints. IEEE 802.11 based infrastructure backhauling mode of WMNs has been considered to formulate the MINLP optimization problem. Proposed method gives the full routing and scheduling procedure in WMN in order to obtain mentioned goals.

Keywords: Mixed-Integer Non Linear Programming (MINLP), routing and scheduling, throughput, wireless mesh networks (WMNs)

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Authors: A. Pedram, M. R. Jamali, T. Pedram, S. M. Fakhraie, C. Lucas

Abstract:

Local Linear Neuro-Fuzzy Models (LLNFM) like other neuro- fuzzy systems are adaptive networks and provide robust learning capabilities and are widely utilized in various applications such as pattern recognition, system identification, image processing and prediction. Local linear model tree (LOLIMOT) is a type of Takagi-Sugeno-Kang neuro fuzzy algorithm which has proven its efficiency compared with other neuro fuzzy networks in learning the nonlinear systems and pattern recognition. In this paper, a dedicated reconfigurable and parallel processing hardware for LOLIMOT algorithm and its applications are presented. This hardware realizes on-chip learning which gives it the capability to work as a standalone device in a system. The synthesis results on FPGA platforms show its potential to improve the speed at least 250 of times faster than software implemented algorithms.

Keywords: LOLIMOT, hardware, neurofuzzy systems, reconfigurable, parallel.

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