This paper presents a novel training algorithm for fuzzy inference systems. The algorithm combines the Levenberg-Marquardt algorithm with variable structure systems approach. The combination is performed by expressing the parameter update rule in continuous time and application of sliding control method to the gradient based training procedure. In this paper, it is discussed that a fuzzy infere...

This paper reports the development of a second nearest-neighbor modified embedded atom method (2NN MEAM) interatomic potential for lithium (Li). The 2NN MEAM potential contains 14 adjustable parameters. For a given set of these parameters, a number of physical properties of Li were predicted by molecular dynamics (MD) simulations. By fitting these MD predictions to their corresponding values fr...

There has been a growing interest in combining both neural network and fuzzy system, and as a result, neuro-fuzzy computing techniques have been evolved. ANFIS (adaptive network-based fuzzy inference system) model combined the neural network adaptive capabilities and the fuzzy logic qualitative approach. In this paper, a novel structure of unsupervised ANFIS is presented to solve differential e...

The paper presents a new closed-form expression for the fractional Fourier transform of generalized Triangular and Welch window functions. Fractional Fourier Transform (FrFT) is a parameterized transform having an adjustable transform parameter which makes it more flexible and superior over ordinary Fourier transform in several applications. It is an important tool used in signal processing for...

We have proposed an adaptive procedure in order to estimate unknown parameters of a numerical model of a chaotic CO2 laser, which is observed through a time series that represents the output intensity of the laser. To do that, we consider a coupled system with the same functional form and adjustable parameters. The salient feature of the proposed technique is that accurate parameter estimation ...

Consider the problem of selecting the member of a parametrized family of curves that best matches a given curve. This is a key step in determining proper values for adjustable parameters in low-order plasma etching and deposition models. Level set methods o er several attractive features for treating such problems. This paper presents a parameter estimation scheme that exploits the level set fo...

When the parameter of any systems changes with respect to time then the constant gain PI controller action is not effective. In case of MRAC based design the adjustable PI gain parameters corresponding to changes in plant will be determined by referring to reference model specifying the property of desired control system. This paper presents the method to design MRAC based PI controllerfor spee...

We report a successful quantitative account of the experimentally determined electron thermal conductivity chi(e) in a beam-heated H mode plasma by the magnetic fluctuations from microtearing instabilities. The calculated chi(e) based on existing nonlinear theory agrees with the result from transport analysis of the experimental data. Without using any adjustable parameter, the good agreement s...

 A step-by-step algorithm for enhancement of periodic signals that are highly corrupted by additive uncorrelated white gausian noise is proposed. In each adaptation step a new parallel second-order section is added to the previous filters. Every section has only one adjustable parameter, i.e., the center frequency of the self-tuning filter. The bandwidth and the convergence factor of each secti...

The sandpile model, introduced in 1987, was the first model to exhibit self-organized critical behavior, that is, the system moved towards its critical point without the need to tune any adjustable external parameter. In this paper, we look at the why these models exhibit such non-intuitive behavior. We also look at some of the phenomenology near the critical point, such as scaling laws and cri...