Selection on the basis of prior testing

We establish that under mild conditions, testing for the individual significance of an impulse indicator in the conditional model, selected on the basis of prior testing of its significance in the impulse saturated marginal model does not require bootstrapping critical values. Extensive Monte Carlo evidence shows that the real size of a joint F test in the conditional on the block of dummies retained from the marginal is independent of nominal size used for impulse saturation used in the marginal model. The findings are shown to hold for a plethora of dynamic models and sample sizes. Such results are fundamental not only in model selection theory, but also for the emerging class of automatically computable super exogeneity tests.model selection; impulse saturation, super exogeneity; bootstrapping

Low-coverage heteroepitaxial growth with interfacial mixing

We investigate the influence of intermixing on heteroepitaxial growth dynamics, using a two-dimensional point island model, expected to be a good approximation in the early stages of epitaxy. In this model, which we explore both analytically and numerically, every deposited B atom diffuses on the surface with diffusion constant $D_{\rm B}$, and can exchange with any A atom of the substrate at constant rate. There is no exchange back, and emerging atoms diffuse on the surface with diffusion constant $D_{\rm A}$. When any two diffusing atoms meet, they nucleate a point island. The islands neither diffuse nor break, and grow by capturing other diffusing atoms. The model leads to an island density governed by the diffusion of one of the species at low temperature, and by the diffusion of the other at high temperature. We show that these limit behaviors, as well as intermediate ones, all belong to the same universality class, described by a scaling law. We also show that the island-size distribution is self-similarly described by a dynamic scaling law in the limits where only one diffusion constant is relevant to the dynamics, and that this law is affected when both $D_{\rm A}$ and $D_{\rm B}$ play a role.Comment: 16 pages, 6 figure

Homogeneous Spiking Neuromorphic System for Real-World Pattern Recognition

A neuromorphic chip that combines CMOS analog spiking neurons and memristive synapses offers a promising solution to brain-inspired computing, as it can provide massive neural network parallelism and density. Previous hybrid analog CMOS-memristor approaches required extensive CMOS circuitry for training, and thus eliminated most of the density advantages gained by the adoption of memristor synapses. Further, they used different waveforms for pre and post-synaptic spikes that added undesirable circuit overhead. Here we describe a hardware architecture that can feature a large number of memristor synapses to learn real-world patterns. We present a versatile CMOS neuron that combines integrate-and-fire behavior, drives passive memristors and implements competitive learning in a compact circuit module, and enables in-situ plasticity in the memristor synapses. We demonstrate handwritten-digits recognition using the proposed architecture using transistor-level circuit simulations. As the described neuromorphic architecture is homogeneous, it realizes a fundamental building block for large-scale energy-efficient brain-inspired silicon chips that could lead to next-generation cognitive computing.Comment: This is a preprint of an article accepted for publication in IEEE Journal on Emerging and Selected Topics in Circuits and Systems, vol 5, no. 2, June 201

A Pedagogy for Original Synners

Part of the Volume on Digital Young, Innovation, and the UnexpectedThis essay begins by speculating about the learning environment of the class of 2020. It takes place entirely in a virtual world, populated by simulated avatars, managed through the pedagogy of gaming. Based on this projected version of a future-now-in-formation, the authors consider the implications of the current paradigm shift that is happening at the edges of institutions of higher education. From the development of programs in multimedia literacy to the focus on the creation of hybrid learning spaces (that combine the use of virtual worlds, social networking applications, and classroom activities), the scene of learning as well as the subjects of education are changing. The figure of the Original Synner is a projection of the student-of-the-future whose foundational literacy is grounded in their ability to synthesize information from multiple information streams

Multiple Scale-Free Structures in Complex Ad-Hoc Networks

This paper develops a framework for analyzing and designing dynamic networks comprising different classes of nodes that coexist and interact in one shared environment. We consider {\em ad hoc} (i.e., nodes can leave the network unannounced, and no node has any global knowledge about the class identities of other nodes) {\em preferentially grown networks}, where different classes of nodes are characterized by different sets of local parameters used in the stochastic dynamics that all nodes in the network execute. We show that multiple scale-free structures, one within each class of nodes, and with tunable power-law exponents (as determined by the sets of parameters characterizing each class) emerge naturally in our model. Moreover, the coexistence of the scale-free structures of the different classes of nodes can be captured by succinct phase diagrams, which show a rich set of structures, including stable regions where different classes coexist in heavy-tailed and light-tailed states, and sharp phase transitions. Finally, we show how the dynamics formulated in this paper will serve as an essential part of {\em ad-hoc networking protocols}, which can lead to the formation of robust and efficiently searchable networks (including, the well-known Peer-To-Peer (P2P) networks) even under very dynamic conditions

Time-Varying Comovements in Developed and Emerging European Stock Markets: Evidence from Intraday Data

We study comovements between three developed (France, Germany, the United Kingdom) and three emerging (the Czech Republic, Hungary and Poland) European stock markets. The novelty of our paper is that we apply the Dynamic Conditional Correlation GARCH models proposed by Engle (2002) to five-minute tick intraday stock price data for the period from June 2003 to January 2006. We find a strong correlation between the German and French markets and also between these two markets and the UK stock market. By contrast, very little systematic positive correlation can be detected between the Western European stock markets and the three stock markets of Central and Eastern Europe, as well as within the latter group.http://deepblue.lib.umich.edu/bitstream/2027.42/57241/1/wp861 .pd