The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
Oscillatory nonlinear networks represent a circuit architecture for image and information processing. It has been shown that they can be exploited to implement associative and dynamic memories. It has also been shown that phase noise play an important role as a limiting key factor for the performances of oscillatory cells. A tool of paramount importance for the design of oscillatory networks and the...
Spin torque nanodevices could provide a platform for computation beyond Moore's law. The network of spin oscillators can have only local, cellular interconnections because of the underlying physics: the interaction between the oscillators happens through the magnetic field. In this paper we describe the dynamics of weakly coupled spin-torque oscillator networks and how the dynamics of these cellular...
There are a large number of problems which can be accelerated by using architectures on Field Programmable Gate Arrays (FPGA). However sometimes the complexity of a problem does not allow to map it onto a specific FPGA. In that case analysis of precision of the arithmetic unit which may solve the computational problem can be a good attempt to fit the architecture and to accelerate its computation...
Oscillatory networks represent a circuit architecture for image and information processing, that can be used to realize associative and dynamic memories. Phase noise is often a limiting key factors for the performances of oscillatory networks. The ideal framework to investigate phase noise effect in nonlinear oscillators are phase models. Classical phase models lead to the conclusion that, in presence...
In this paper CNN modeling of tsunami waves is presented. Two models are studied: two-component Camassa-Holm type equation is studied and generalized KdV equation. For these cases CNN models are constructed and traveling wave solutions are obtained theoretically and via simulations. New type of traveling wave solutions are introduced — peak type, called peakon. Discussion and example of tsunami waves...
In this paper we first present a novel, simple and general boundary condition-based model for nano-scale switching resistances with memory. The boundary conditions are embedded into a switching function modulating the rate of ionic transport, and, on the basis of the memristor under modeling, may be suitably chosen through an optimization procedure minimizing some reference parameter such as the mean...
The CNN (Cellular Neural Network) is a powerful image processing architecture whose hardware implementation is extremely fast. The lack of such hardware device in a development process can be substituted by using an efficient simulator implementation. Commercially available graphics cards with high computing capabilities make this simulator feasible. The aim of this work is to present a GPU based...
Time-Derivative CNNs (TDCNNs) have been recently proposed as a novel paradigm realizing spatiotemporal transfer functions for linear filtering. Their dynamics is usually simulated with SIMULINK because VLSI chips are still in the preliminary phase. In order to make TDCNNs available to a larger audience, we present here their implementation on a Xilinx Spartan-6 FPGA. The results concerning an 8×8...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.