Search

The article describes the solution to the problem of stabilizing a nonlinear system using machine learning methods. Neural networks are one of the promising directions in this area. The article describes a model of spiking neural network, which differs from previous generations of networks by its similarity to biological neurons. A pendulum on an elastic foundation was chosen as a dynamic system for the study. The input layer of the neural network is the so-called sensory neuron, and information about the deviation of the pendulum from the equilibrium position was received on it. The Leaky Integrate-and-Fire model of the spiking neural network was used. The article shows the process of stabilization of a pendulum on an elastic foundation. The closed system was built and a method for a numerical solution was implemented. Two configurations of control functions have been considered. It is shown that the time required to bring the system into a steady equilibrium state depends on the choice of the control function. more...

The volumetric distribution of bone tissue can be analysed in terms of orthotropic medium. In this case, it is important to define the orthotropic directions. Nowadays, computed tomography methods allow getting such information. The method for automation such analysis is presented. Firstly, the threshold of binarization should be calculated. Then the sample should be meshed and each element should be binarized. After that fabric tensor, eigenvalues, eigenvectors and fractional anisotropy can be calculated for each element. Statistical methods were used to analyse the field of the obtained data. Described methods were used on a bone sample. It was shown that for a sample the fabric tensor is constant and the fractional anisotropy is close to zero. That’s means that the medium in the sample was isotropic. more...

In the paper, a method for the direct image-based creation of the finite element model from images is presented. Image information is taken into account during the calculation of the element stiffness matrix. In this case, material heterogeneity can be included directly in the finite element model. For this purpose, the hypothesis about the correlation between pixel values and elastic properties was used. Four nodes plane element was built. The element can be used with the quantitative phase or scanning electron images and computed tomography data. Simulation for bone data performed. The influence of pixel on the error estimate was studied. The method to parallelize the calculation of the stiffness matrix is presented. As an example, a slice of bone was used in the calculation. Results for average stress distribution for the origin and improved mesh are presented. more...