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Annual International Conference of the IEEE engineering in Medicine and Biology Society

作者： Matthew D. Burns Nima Bigdely-Shamlo Nathaniel J. Smith Kenneth Kreutz-Delgado Scott Makeig Dept. of Electrical and Computer Engineering University of California School of Informatics University of Edinburgh Informatics Forum Swartz Center for Computational Neuroscience (SCCN) of the Institute for Neural Computation (INC) University of California

ISBN: (纸本)9781457702150

The traditional method of estimating an Event Related Potential (ERP) is to take the average of signal epochs time locked to a set of similar experimental events. This averaging method is useful as long as the experimental procedure can sufficiently isolate the brain or non-brain process of interest. However, if responses from multiple cognitive processes, time locked to multiple classes of closely spaced events, overlap in time with varying inter-event intervals, averaging will most likely fail to identify the individual response time courses. For this situation, we study estimation of responses to all recorded events in an experiment by a single model using standard linear regression (the rERP technique). Applied to data collected during a Rapid Serial Visual Presentation (RSVP) task, our analysis shows: (1) The rERP technique accounts for more variance in the data than averaging when individual event responses are highly overlapping;(2) the variance accounted for by the estimates is concentrated into a fewer ICA components than raw EEG channel signals.

关键词： Event-related potentials averaging TRADITIONAL METHODS processing time Reaction Time

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Transfer Learning across Networks for Collective Classification

Transfer Learning across Networks for Collective Classificat...

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IEEE International Conference on Data Mining (ICDM)

作者： Meng Fang Jie Yin Xingquan Zhu Centre for Quantum Computation & Intelligent Systems University of Technology Sydney Australia Computational Informatics CSIRO Australia Dept. of Computer & Electrical Engineering and Computer Science Florida Atlantic University USA

ISBN: (纸本)9781479913282

This paper addresses the problem of transferring useful knowledge from a source network to predict node labels in a newly formed target network. While existing transfer learning research has primarily focused on vector-based data, in which the instances are assumed to be independent and identically distributed, how to effectively transfer knowledge across different information networks has not been well studied, mainly because networks may have their distinct node features and link relationships between nodes. In this paper, we propose a new transfer learning algorithm that attempts to transfer common latent structure features across the source and target networks. The proposed algorithm discovers these latent features by constructing label propagation matrices in the source and target networks, and mapping them into a shared latent feature space. The latent features capture common structure patterns shared by two networks, and serve as domain-independent features to be transferred between networks. Together with domain-dependent node features, we thereafter propose an iterative classification algorithm that leverages label correlations to predict node labels in the target network. Experiments on real-world networks demonstrate that our proposed algorithm can successfully achieve knowledge transfer between networks to help improve the accuracy of classifying nodes in the target network.

关键词： Subspace constraints Knowledge engineering Prediction algorithms Convergence Optimization Iterative methods Knowledge transfer

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Evolving complex networks: A model for the integration/segregation phenomena

Evolving complex networks: A model for the integration/segre...

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3rd IFAC Conference on Analysis and Control of Chaotic systems, CHAOS 2012

作者： Avalos-Gaytán, Vanesa Almendral, Juan A. Schaeffer, Satu Elisa Boccaletti, Stefano Postgraduate Division in Systems Engineering Dept. of Mechanical and Electrical Engineering Universidad Autónoma de Nuevo Leon San-Nicolas de los Garza NL Mexico Complex Systems Group Dept. Tecnología Electrónica Universidad Rey Juan Carlos Calle Tulipán s/n 28933 Móstoles Madrid Spain Postgraduate Division in Computation and Mechatronics Dept. of Mechanical and Electrical Engineering Universidad Autónoma de Nuevo León San-Nicolás de los Garza NL Mexico Group of Computational Systems Biology Center for Biomedical Technology 28223 Pozuelo de Alarcón Madrid Spain

ISBN: (纸本)9783902823021

We study the integration/segregation problem from the viewpoint of complex networks, but considering that the network topology is not static but there is an adaptive mechanism acting on the links. Our goal is to identify under which conditions network synchronization occurs and what structural properties are present in the network topology when this happens. In particular, we experimentally compute the main descriptive structural properties of the network when it has been modified with the proposed mechanism, and it is elucidated the relationship between these results and the observed synchronization at both the local and global scale. Our main finding is that modularity, a global feature, can naturally emerge in a network when evolving links are considered, that is, by means of dynamical properties at the local scale. © 2012 IFAC.

关键词： Synchronization

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Evolving complex networks: A model for the integration/segregation phenomena *

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IFAC Proceedings Volumes 2012年第12期45卷 66-69页

作者： Vanesa Avalos-Gaytán Juan A. Almendral Satu Elisa Schaeffer Stefano Boccaletti Postgraduate Division in Systems Engineering Dept. of Mechanical and Electrical Engineering Universidad Autánoma de Nuevo León San Nicolás de los Garza NL Mexico Complex Systems Group Dept. Tecnología Electrónica Universidad Rey Juan Carlos Calle Tulipán s/n 28933 Móstoles Madrid Spain Postgraduate Division in Computation and Mechatronics Dept. of Mechanical and Electrical Engineering Universidad Autóanoma de Nuevo Leóan San Nicolás de los Garza NL Mexico Group of Computational Systems Biology Center for Biomedical Technology 28223 Pozuelo de Alarcaón Madrid Spain

关键词： Complex networks modularity synchronization

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Evaluation of a Closed Loop Inductive Power Transmission System on an Awake Behaving Animal Subject

Evaluation of a Closed Loop Inductive Power Transmission Sys...

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Annual International Conference of the IEEE engineering in Medicine and Biology Society

作者： Mehdi Kiani Ki Yong Kwon Fei Zhang Karim Oweiss Maysam Ghovanloo GT-Bionics Lab School of Electrical and Computer Engineering at Georgia Institute of Technology Neural Systems Engineering Lab ECE Dept. College of Eng. at Michigan State University ECE Dept. and Neuroscience Program at Michigan State University

ISBN: (纸本)9781424441211

This paper presents in vivo experimental results for a closed loop wireless power transmission system to implantable devices on an awake behaving animal subject. In this system, wireless power transmission takes place across an inductive link, controlled by a commercial off-the-shelf (COTS) radio frequency identification (RFID) transceiver (TRF7960) operating at 13.56 MHz. Induced voltage on the implantable secondary coil is rectified, digitized by a 10-bit analog to digital converter, and transmitted back to the primary via back telemetry. Transmitter (Tx) and receiver (Rx) circuitry were mounted on the back of an adult rat with a nominal distance of ～7 mm between their coils. Our experiments showed that the closed loop system was able to maintain the Rx supply voltage at the designated 3.8 V despite changes in the coils' relative distance and alignment due to animal movements. The Tx power consumption changed between 410 ～ 560 mW in order to deliver 27 mW to the receiver. The open loop system, on the other hand, showed undesired changes in the Rx supply voltage while the Tx power consumption was constant at 660 mW.

关键词： Coils Inductive power transmission Closed loop systems awake Induction loop systems analog digital converter supply voltage Power consumption Implants and Prostheses Contraceptive Coil Radio frequency identification Back Open loop systems Digitizers

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Electro-magnetic sensing and actuation array on silicon substrate platforms

Electro-magnetic sensing and actuation array on silicon subs...

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IEEE Nanotechnology Materials and Devices Conference

作者： Abu-Nimeh, Faisal T. Salem, Fathi M. Circuits Systems and Neural Networks Lab Dept. of Electrical and Computer Engineering Michigan State University East Lansing United States

ISBN: (纸本)9781424488964

Electromagnetic arrays can be precisely constructed on silicon CMOS technology as a platform for collective non-contact sensing and manipulation of magnetic or magnetized particles of micron to nano scale. Such platforms become a tool to interact with nano scale particles on the silicon substrate and enable direct interface to measurement and computing devices. This paper overviews current efforts along this direction and presents an example design of a platform for sensing and manipulating magnetized beads on its surface using standard silicon CMOS technology. The vision is that such arrays can be easily commanded in nano seconds to realize magnetic field profiles in order to steer magnetized material in the proximity of the platform. Moreover, as technology features decrease, the size of the electromagnetic coil cells in the array would also decrease to nano scale, sharpening the sensing and manipulation resolution of the platforms. © 2010 IEEE.

关键词： Interfaces (materials)

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Scalable event routing in hierarchical neural array architecture with global synaptic connectivity

Scalable event routing in hierarchical neural array architec...

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2010 12th International Workshop on Cellular Nanoscale Networks and their Applications, CNNA 2010

作者： Joshi, Siddharth Deiss, Steve Arnold, Mike Park, Jongkil Yu, Theodore Cauwenberghs, Gert Dept. of Electrical and Computer Engineering UC San Diego United States Dept. of Bioengineering UC San Diego United States Institute for Neural Computation UC San Diego United States Computational Neurobiology Laboratory Salk Institute United States

ISBN: (纸本)9781424466795

An asynchronous communication scheme for scalable routing of spike events in large-scale neuromorphic hardware is presented. The routing scheme extends the Address- Event Representation (AER) protocol for spike event communication to a modular, hierarchical architecture supporting efficient implementation of global synaptic inter-connectivity across a cellular matrix of message parsing axonal relay nodes at varying spatial scales. This paper presents a probabilistic framework for analyzing trade-offs in throughput and latency of synaptic communication as a function of load and geometry, and simulation results verifying the statistics of traffic flow across the architecture. © 2010 IEEE.

关键词： Network architecture

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Integrated magnetic array for bio-object sensing and manipulation

Integrated magnetic array for bio-object sensing and manipul...

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IEEE Biomedical Circuits and systems (BIOCAS)

作者： Faisal T. Abu-Nimeh M. Salem Fathi Circuits Systems and Neural Networks Lab Dept. of Electrical & Computer Engineering Michigan State University East Lansing USA Dept. of Electrical & Computer Engineering Michigan State University East Lansing USA

Magnetic molecular-level interrogation, manipulation, and diagnosis are emerging as lab-on-chip platforms. These platforms entail low-cost, low-power, portable, and high efficiency integrated implementations. We introduce an all-integrated programmable 16 × 16 magnetic coil array chip for sensing and actuating small single bio-objects or collaboratively manipulating larger ones. The die-size is 1.5 × 1.5 mm 2 designed in bulk 0.5 μm CMOS technology. The integrated design does not require any external magnetic source. It relies on the Hall effect generated by the smallest permissible vertical coil inductors (in this reported technology, the smallest inductor's planar area is 6 μm × 6 μm). The coil array is selectively and dynamically controlled. Each cell, composed of the coil and its logical control circuitry, can detect small objects in the order of 1μm diameter as well as emit eight programmable magnetic field levels for manipulation. All array sensing and driving components are shared to reduce the overall imprint. Also, they are tuned to work at 900 MHz incorporating high-speed serial row/column switching for seamless pseudoparallel operation.

关键词： Coils Arrays Magnetic separation Sensors Oscillators Switches Magnetic circuits

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A Proposal to Stabilize the Random Waypoint Mobility Model for Ad Hoc Network Simulation

A Proposal to Stabilize the Random Waypoint Mobility Model f...

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IEEE Conference on Wireless Communications and Networking

作者： Renato M. de Moraes Fagner P. de Araújo Alisson S. L. Pontes Dept. of Electrical Engineering University of Brasília (UnB) Brasília Brasília DF Brazil Dept. of Computing and Systems University of Pernambuco (UPE) Recife PE Brazil Institute of Computation State University of Campinas (UNICAMP) Campinas Sao Paulo SP Brazil

It has been recently shown that the instantaneous average node speed for the random waypoint (RWP) mobility model may not reach a steady state regime due to velocity gradual decaying which can cause inaccurate results in simulations and communication protocol validations for mobile ad hoc networks (MANETs). This paper presents a modification to the RWP model, in which we propose to choose node speeds from a BETA(2,2) distribution, demonstrating analytically and by simulations that our idea stabilizes the instantaneous average node speed and consequently other important network metrics, like control overhead, number of dropped data packets and delivery delay. The proposal of alteration not only eliminates the decaying problem of the average node speed but also provides average values closer to the commonly supposed average velocity (V max + V min )/2 than those of the original RWP model. In addition, the proposed change for the RWP model can be readily incorporated into network simulators.

关键词： Proposals Ad hoc networks Peer to peer computing Steady-state Protocols Mobile ad hoc networks Performance analysis computational modeling Computer networks Mobile communication

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International Journal of Computer Vision: Guest Editorial

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International Journal of Computer Vision 2008年第1-3期77卷 1-1页

作者： Freeman, William Perona, Pietro Scholkopf, Bernhard Dept. of Electrical Engineering and Computer Science Massachusetts Institute of Technology Cambridge MA 02139 United States Dept. of Electrical Engineering and Computation and Neural Systems California Institute of Technology Pasadena CA 91125 United States Dept. of Empirical Inference Max Planck Institute for Biological Cybernetics Tübingen 72076 Germany

No abstract available

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