On the validity of memristor modeling in the neural network literature

An analysis of the literature shows that there are two types of non-memristive models that have been widely used in the modeling of so-called "memristive" neural networks. Here, we demonstrate that such models have nothing in common with the concept of memristive elements: they describe either non-linear resistors or certain bi-state systems, which all are devices without memory. Therefore, the results presented in a significant number of publications are at least questionable, if not completely irrelevant to the actual field of memristive neural networks

Synchronization of a class of fractional-order neural networks with multiple time delays by comparison principles

This paper studies the synchronization of fractional-order neural networks with multiple time delays. Based on an inequality of fractional-order and comparison principles of linear fractional equation with multiple time delays, some sufficient conditions for synchronization of master-slave systems are obtained. Example and related simulations are given to demonstrate the feasibility of the theoretical results

Impulsive control of nonlinear systems with impulse time window and bounded gain error

In this paper, we establish a new sufficient condition for the stability of impulsive systems with impulse time window and bounded gain error. The proposed result is more general and more applicable than some existing results. Finally, a numerical example is given to show the effectiveness of our result

High-Speed CMOS-Free Purely Spintronic Asynchronous Recurrent Neural Network

Neuromorphic computing systems overcome the limitations of traditional von Neumann computing architectures. These computing systems can be further improved upon by using emerging technologies that are more efficient than CMOS for neural computation. Recent research has demonstrated memristors and spintronic devices in various neural network designs boost efficiency and speed. This paper presents a biologically inspired fully spintronic neuron used in a fully spintronic Hopfield RNN. The network is used to solve tasks, and the results are compared against those of current Hopfield neuromorphic architectures which use emerging technologies

Fixed-time control of delayed neural networks with impulsive perturbations

This paper is concerned with the fixed-time stability of delayed neural networks with impulsive perturbations. By means of inequality analysis technique and Lyapunov function method, some novel fixed-time stability criteria for the addressed neural networks are derived in terms of linear matrix inequalities (LMIs). The settling time can be estimated without depending on any initial conditions but only on the designed controllers. In addition, two different controllers are designed for the impulsive delayed neural networks. Moreover, each controller involves three parts, in which each part has different role in the stabilization of the addressed neural networks. Finally, two numerical examples are provided to illustrate the effectiveness of the theoretical analysis

Stability analysis for delayed quaternion-valued neural networks via nonlinear measure approach

In this paper, the existence and stability analysis of the quaternion-valued neural networks (QVNNs) with time delay are considered. Firstly, the QVNNs are equivalently transformed into four real-valued systems. Then, based on the Lyapunov theory, nonlinear measure approach, and inequality technique, some sufficient criteria are derived to ensure the existence and uniqueness of the equilibrium point as well as global stability of delayed QVNNs. In addition, the provided criteria are presented in the form of linear matrix inequality (LMI), which can be easily checked by LMI toolbox in MATLAB. Finally, two simulation examples are demonstrated to verify the effectiveness of obtained results. Moreover, the less conservatism of the obtained results is also showed by two comparison examples

Zeitsynchronisation in drahtgebundenen Rechnernetzen

Ausgehend von einer Analyse des Standes der Technik werden neuartige Verfahren für die Zeitsynchronisation in drahtgebundenen Netzwerken vorgestellt. Unter anderem wird, zum ersten Mal im Bereich der Zeitsynchronisation, eine Kombination aus Linearer Optimierung und Broadcast-Nachrichten vorgestellt, was eine Verbindung der jeweiligen Genauigkeits- und Skalierbarkeitsvorteile ermöglicht. Weiterhin wird, ebenfalls zum ersten Mal im Bereich der Zeitsynchronisation, eine Kombination aus Linearer Optimierung und Temperaturkompensation vorgestellt.Based on an analysis of the state of the art, several new time synchronization methods for wired networks are proposed. Among others, for the first time in the synchronization domain, a combination of linear programming and broadcast messages is proposed, which allows combining the respective accuracy and scalability advantages. Moreover, this thesis proposes combining linear programming and temperature compensation, also for the first time in the field of time synchronization