In this paper, threshold voltage modeling based on neural networks is presented. The database was obtained by performing DC analysis with possible combinations of MOSFETs terminal voltages and channel widths which directly effect threshold voltage values in submicron technology. The neural network was trained with the database including 0.25 µm and 0.40 µm TSMC process parameters. In order to prove the extrapolation ability, the test dataset is constituted with 0.18 µm TSMC process parameters, which were not applied to the neural network for training. The test results of neural network tool are compared with the data obtained by using the Cadence simulation tool. The excellent agreement between the experimental and the model results makes neural networks a powerful tool for estimation o...
Tracking moving objects is a vital visual task for the survival of an animal. We describe oscillatory neural network models of visual attention with a central element that can track a moving target among a set of distracters on the screen. At the initial stage, the model forms the focus of attention on an arbitrary object that is considered as a target. Other objects are treated as distracters. We present here two models: 1) synchronisation based model designed as a network of phase oscillators and 2) spiking neural model which is based on the idea of resource-limited parallel visual pointers. Selective attention and the tracking process are represented by the partial synchronisation between the central unit and a subgroup of peripheral elements. Simulation results are in overall agreem...
.... Toward a Model of Knowledge Transfer Success . When discussing th.... Repenning, N. P. (2002). A simulation-based approach to understanding the dynamics of in...
In this paper we present the design and implementation of an hyper-heuristic for efficiently scheduling independent jobs in Computational Grids. An efficient scheduling of jobs to Grid resources depends on many parameters, among others, the characteristics of the resources and jobs (such as computing capacity, consistency of computing, workload, etc.). Moreover, these characteristics change over time due to the dynamic nature of Grid environment, therefore the planning of jobs to resources should be adaptively done. Existing ad hoc scheduling methods (batch and immediate mode) have shown their efficacy for certain types of resource and job characteristics. However, as stand alone methods, they are not able to produce the best planning of jobs to resources for different types of Grid res...
... of independent tasks (Monte Carlo simulations, parameter-space searches, etc.), also known as ta... [8] used GAs for developing two prediction models for the completion time of jobs in a service Grid....
... invariance was tested by constraining model parameters to be equal across the two groups and e...Based on extensive simulation studies, these authors have proposed revised criti...
The main aim of this paper is to forecast gold and silver daily returns with advanced regression analysis using various linear and non-linear models. ARMA models are used as a linear benchmark for comparison purposes with established non-linear models such as Nearest Neighbours and MultiLayer Perceptron (MLP), and Higher Order Neural Networks (HONN) whose application to financial markets is quite new. All models are assessed using statistical criteria such as correct directional change as well as financial criteria such as risk adjusted return. The main aim is to find which of these models generate the best returns and if nonlinear models can be used for generating excess returns in the precious metals market. This is achieved by implementing a trading simulation where the forecast is t...
Tight labour markets and changing employment relationships make employees with high levels of firm-specific knowledge, skills, and abilities less dependent on and committed to their employer. Companies need to work harder in order to attract and retain employees and protect their mutual human capital investments. Using a dataset with survey data from employees in 11 companies (N = 777), the present study shows evidence that employee share ownership, provided that it is taken seriously as reflected by the presence of a small number of other HRM practices in the company, might be a worthwhile avenue for managers to explore.
... develop further their company's latest simulation software to test the strength of new materials the... should therefore be part of this kind of models that include employee share ownership. I therefore...
The article offers a new view on the organization of the processes of human perception. It introduces the concept of inclusive sensory characteristic, which is a response of a given perceptual level to those features or characteristics of an underlying level whose spatial organization or specific temporal succession constitutes an adaptively meaningful entity. The sequence of inclusive characteristics forms a hierarchy: from features to the highest inclusive characteristics which bind sensory data into unified images and scenes. The highest inclusive characteristic is neither an image nor a scene, but a unique scheme of combination of underlying-level objects, which produces the image or the scene. Specific patterns of electric activity, which map inclusive characteristics, are relayed ...
...A computer simulation of perception confirms that the proposed model wor...
This article presents a design of model of the medium access control (MAC) of a sub-layer of a Controller Area Network (CAN) protocol (CAN is the most widely used in-vehicle network). The model is created via hierarchical Coloured Petri Nets. For better clarity and comprehension, the wide created model is divided into submodules. An application CPN Tools, developed by the CPN group at the University of Aarhus (Denmark), is used as a modelling tool. This model expresses the whole CAN's fault confinement mechanisms and the other functions of MAC sub-layer such as data encapsulation, frame coding (stuffing/de-stuffing), medium access management and acknowledgement. Functionality of the originally created model was tested by a series of ad hoc simulations in the model environment. The asset...
Associative neural network models are a commonly used methodology when investigating the theory of associative memory in the brain. Comparisons between the mammalian hippocampus and associative memory models of neural networks have been investigated [12]. Biologically based networks are systems built of complex biologically realistic cells with a variety of properties. Here we compare and contrast associative memory function in a network of biologically-based spiking neurons [22] with previously published results for a simple artificial neural network model [11]. We shall focus primarily on the recall process from a memory where patterns have previously been stored by Hebbian learning. We investigate biologically plausible implementations of methods for improving recall under biological...
... simulated using the NEURON computer simulation package [5] . Details of the individual cell model...
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arbeitserlaubnis bulgarien | lateinamerika studien | 70 221 ewg | affective | Arbeitsunfähigkeit | principio de eficacia derecho | ausência nexo causalidade | Eje comunitario | Charte africaine des droits de l'homme et des peuples | artistas da arte moderna
