SUMMARY The paper addresses the determination of high order Volterra transfer functions of non-linear mul-tiport networks containing multidimensional non-linear elements. A new method is developed for utilizing parallel computing which is very efficient for approximately 10–20 processors. The utilization of each processor may be as high as 80–95 %. The developed program is very flexible as it i...

Off‐pump Coronary Artery Bypass Graft (CABG) surgery outperforms traditional on‐pump surgery because the assisted robotic tools can alleviate the relative motion between the beating heart and robotic tools. Therefore, it is possible for the surgeon to operate on the beating heart and thus lessens post surgery complications for the patients. Due to the highly irregula...

Equalization of satellite communication using complex-bilinear recurrent neural network (C-BLRNN) is proposed. Since the BLRNN is based on the bilinear polynomial, it can be used in modeling highly nonlinear systems with time-series characteristics more effectively than multilayer perceptron type neural networks (MLPNN). The BLRNN is first expanded to its complex value version (C-BLRNN) for dea...

Abstract: This article focuses on obtaining analytical solutions for d-dimensional, parabolic Volterra integro-differential equations with different types of frictional memory kernel. Based on Laplace transform and Fourier transform theories, the properties of the Fox-H function and convolution theorem, analytical solutions for the equations in the infinite domain are derived under three fricti...

This paper presents a comparative analysis of various linear and nonlinear equalizers for a high density optical channel. Since the read-out process is nonlinear, a suitable model basedon the Volterra series has been adopted. In this work, we compare the performance and complexity of equalizers designed for linear and nonlinear channels. Specifically, Adaptive Minimum Mean Square Error (MSE), A...

Digital compensation of nonlinear distortion due to nonlinear characteristic of electronic or electromechanical device is becoming more and more important. This paper considers Direct Learning Architectures (DLAs) for predistortion of nonlinear systems described using Volterra series. The adaptive predistorter which is connected in tandem with the nonlinear system can be modeled as a Volterra f...

This work tackles the problem of expanding Volterra models using Laguerre functions. A strict global optimal solution is derived when each multidimensional kernel of the model is decomposed into a set of independent orthonormal bases, each of which parameterized by an individual Laguerre pole intended for representing the dominant dynamic of the kernel along a particular dimension. It is proved...

We propose the identification method based on input-output measurements. Our approach exploits the Volterra functional series expansion for empirical “black-box” characterization of non-linear dynamic systems with memory. Procedure of transfer functions identification involves numerical solution of the special Volterra integral equations derived by the parametric family of input sequences with ...

This paper is devoted to the blind identification problem of a special class of nonlinear systems, namely, Volterra models, using a real-coded genetic algorithm (RCGA). The model input is assumed to be a stationary Gaussian sequence or an independent identically distributed (i.i.d.) process. The order of the Volterra series is assumed to be known. The fitness function is defined as the differen...

Abstract In this paper, the representation of the exact solution to the nonlinear Volterra-Fredholm integral equations will be obtained in the reproducing kernel space. The exact solution is represented in the form of series. Its approximate solution is obtained by truncating the series and a new numerical approximate method is obtained. The error of the approximate solution is monotone deceasi...