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2001


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Enhanced User Authentication through Typing Biometrics with Artificial Neural Networks and K-Nearest Neighbor Algorithm

Wong, FWMH., Supian, ASM., Ismail, AF., Lai, WK., Ong, CS.

In 2001 (inproceedings)

ei

[BibTex]

2001


[BibTex]


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Predicting the Nonlinear Dynamics of Biological Neurons using Support Vector Machines with Different Kernels

Frontzek, T., Lal, TN., Eckmiller, R.

In Proceedings of the International Joint Conference on Neural Networks (IJCNN'2001) Washington DC, 2, pages: 1492-1497, Proceedings of the International Joint Conference on Neural Networks (IJCNN'2001) Washington DC, 2001 (inproceedings)

Abstract
Based on biological data we examine the ability of Support Vector Machines (SVMs) with gaussian, polynomial and tanh-kernels to learn and predict the nonlinear dynamics of single biological neurons. We show that SVMs for regression learn the dynamics of the pyloric dilator neuron of the australian crayfish, and we determine the optimal SVM parameters with regard to the test error. Compared to conventional RBF networks and MLPs, SVMs with gaussian kernels learned faster and performed a better iterated one-step-ahead prediction with regard to training and test error. From a biological point of view SVMs are especially better in predicting the most important part of the dynamics, where the membranpotential is driven by superimposed synaptic inputs to the threshold for the oscillatory peak.

ei

PDF [BibTex]

PDF [BibTex]


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Computationally Efficient Face Detection

Romdhani, S., Torr, P., Schölkopf, B., Blake, A.

In Computer Vision, ICCV 2001, vol. 2, (73):695-700, IEEE, 8th International Conference on Computer Vision, 2001 (inproceedings)

ei

DOI [BibTex]

DOI [BibTex]


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Design and Verification of Supervisory Controller of High-Speed Train

Yoo, SP., Lee, DY., Son, HI.

In IEEE International Symposium on Industrial Electronics, pages: 1290-1295, IEEE Operations Center, Piscataway, NJ, USA, IEEE International Symposium on Industrial Electronics (ISIE), 2001 (inproceedings)

Abstract
A high-level controller, supervisory controller, is required to monitor, control, and diagnose the low-level controllers of the high-speed train. The supervisory controller controls low-level controllers by monitoring input and output signals, events, and the high-speed train can be modeled as a discrete event system (DES). The high-speed train is modeled with automata, and the high-level control specification is defined. The supervisory controller is designed using the high-speed train model and the control specification. The designed supervisory controller is verified and evaluated with simulation using a computer-aided software engineering (CASE) tool, Object GEODE

ei

Web DOI [BibTex]

Web DOI [BibTex]


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The psychometric function: II. Bootstrap-based confidence intervals and sampling

Wichmann, F., Hill, N.

Perception and Psychophysics, 63 (8), pages: 1314-1329, 2001 (article)

ei

PDF [BibTex]

PDF [BibTex]


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Towards Learning Path Planning for Solving Complex Robot Tasks

Frontzek, T., Lal, TN., Eckmiller, R.

In Proceedings of the International Conference on Artificial Neural Networks (ICANN'2001) Vienna, pages: 943-950, Proceedings of the International Conference on Artificial Neural Networks (ICANN'2001) Vienna, 2001 (inproceedings)

Abstract
For solving complex robot tasks it is necessary to incorporate path planning methods that are able to operate within different high-dimensional configuration spaces containing an unknown number of obstacles. Based on Advanced A*-algorithm (AA*) using expansion matrices instead of a simple expansion logic we propose a further improvement of AA* enabling the capability to learn directly from sample planning tasks. This is done by inserting weights into the expansion matrix which are modified according to a special learning rule. For an examplary planning task we show that Adaptive AA* learns movement vectors which allow larger movements than the initial ones into well-defined directions of the configuration space. Compared to standard approaches planning times are clearly reduced.

ei

PDF [BibTex]

PDF [BibTex]


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Learning to predict the leave-one-out error of kernel based classifiers

Tsuda, K., Rätsch, G., Mika, S., Müller, K.

In International Conference on Artificial Neural Networks, ICANN'01, (LNCS 2130):331-338, (Editors: G. Dorffner, H. Bischof and K. Hornik), International Conference on Artificial Neural Networks, ICANN'01, 2001 (inproceedings)

ei

PDF [BibTex]

PDF [BibTex]


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A kernel approach for vector quantization with guaranteed distortion bounds

Tipping, M., Schölkopf, B.

In Artificial Intelligence and Statistics, pages: 129-134, (Editors: T Jaakkola and T Richardson), Morgan Kaufmann, San Francisco, CA, USA, 8th International Conference on Artificial Intelligence and Statistics (AI and STATISTICS), 2001 (inproceedings)

ei

[BibTex]

[BibTex]


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The psychometric function: I. Fitting, sampling and goodness-of-fit

Wichmann, F., Hill, N.

Perception and Psychophysics, 63 (8), pages: 1293-1313, 2001 (article)

Abstract
The psychometric function relates an observer'sperformance to an independent variable, usually some physical quantity of a stimulus in a psychophysical task. This paper, together with its companion paper (Wichmann & Hill, 2001), describes an integrated approach to (1) fitting psychometric functions, (2) assessing the goodness of fit, and (3) providing confidence intervals for the function'sparameters and other estimates derived from them, for the purposes of hypothesis testing. The present paper deals with the first two topics, describing a constrained maximum-likelihood method of parameter estimation and developing several goodness-of-fit tests. Using Monte Carlo simulations, we deal with two specific difficulties that arise when fitting functions to psychophysical data. First, we note that human observers are prone to stimulus-independent errors (or lapses ). We show that failure to account for this can lead to serious biases in estimates of the psychometric function'sparameters and illustrate how the problem may be overcome. Second, we note that psychophysical data sets are usually rather small by the standards required by most of the commonly applied statistical tests. We demonstrate the potential errors of applying traditional X^2 methods to psychophysical data and advocate use of Monte Carlo resampling techniques that do not rely on asymptotic theory. We have made available the software to implement our methods

ei

PDF [BibTex]

PDF [BibTex]


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Tracking a Small Set of Experts by Mixing Past Posteriors

Bousquet, O., Warmuth, M.

In Proceedings of the 14th Annual Conference on Computational Learning Theory, Lecture Notes in Computer Science, 2111, pages: 31-47, Proceedings of the 14th Annual Conference on Computational Learning Theory, Lecture Notes in Computer Science, 2001 (inproceedings)

Abstract
In this paper, we examine on-line learning problems in which the target concept is allowed to change over time. In each trial a master algorithm receives predictions from a large set of $n$ experts. Its goal is to predict almost as well as the best sequence of such experts chosen off-line by partitioning the training sequence into $k+1$ sections and then choosing the best expert for each section. We build on methods developed by Herbster and Warmuth and consider an open problem posed by Freund where the experts in the best partition are from a small pool of size $m$. Since $k>>m$ the best expert shifts back and forth between the experts of the small pool. We propose algorithms that solve this open problem by mixing the past posteriors maintained by the master algorithm. We relate the number of bits needed for encoding the best partition to the loss bounds of the algorithms. Instead of paying $\log n$ for choosing the best expert in each section we first pay $\log {n\choose m}$ bits in the bounds for identifying the pool of $m$ experts and then $\log m$ bits per new section. In the bounds we also pay twice for encoding the boundaries of the sections.

ei

PDF PostScript [BibTex]

PDF PostScript [BibTex]


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Learning and Prediction of the Nonlinear Dynamics of Biological Neurons with Support Vector Machines

Frontzek, T., Lal, TN., Eckmiller, R.

In Proceedings of the International Conference on Artificial Neural Networks (ICANN'2001), pages: 390-398, Proceedings of the International Conference on Artificial Neural Networks (ICANN'2001), 2001 (inproceedings)

Abstract
Based on biological data we examine the ability of Support Vector Machines (SVMs) with gaussian kernels to learn and predict the nonlinear dynamics of single biological neurons. We show that SVMs for regression learn the dynamics of the pyloric dilator neuron of the australian crayfish, and we determine the optimal SVM parameters with regard to the test error. Compared to conventional RBF networks, SVMs learned faster and performed a better iterated one-step-ahead prediction with regard to training and test error. From a biological point of view SVMs are especially better in predicting the most important part of the dynamics, where the membranpotential is driven by superimposed synaptic inputs to the threshold for the oscillatory peak.

ei

PDF [BibTex]

PDF [BibTex]


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Estimating a Kernel Fisher Discriminant in the Presence of Label Noise

Lawrence, N., Schölkopf, B.

In 18th International Conference on Machine Learning, pages: 306-313, (Editors: CE Brodley and A Pohoreckyj Danyluk), Morgan Kaufmann , San Fransisco, CA, USA, 18th International Conference on Machine Learning (ICML), 2001 (inproceedings)

ei

Web [BibTex]

Web [BibTex]


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A Generalized Representer Theorem

Schölkopf, B., Herbrich, R., Smola, A.

In Lecture Notes in Computer Science, Vol. 2111, (2111):416-426, LNCS, (Editors: D Helmbold and R Williamson), Springer, Berlin, Germany, Annual Conference on Computational Learning Theory (COLT/EuroCOLT), 2001 (inproceedings)

ei

[BibTex]

[BibTex]


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Unsupervised Segmentation and Classification of Mixtures of Markovian Sources

Seldin, Y., Bejerano, G., Tishby, N.

In The 33rd Symposium on the Interface of Computing Science and Statistics (Interface 2001 - Frontiers in Data Mining and Bioinformatics), pages: 1-15, 33rd Symposium on the Interface of Computing Science and Statistics (Interface - Frontiers in Data Mining and Bioinformatics), 2001 (inproceedings)

Abstract
We describe a novel algorithm for unsupervised segmentation of sequences into alternating Variable Memory Markov sources, first presented in [SBT01]. The algorithm is based on competitive learning between Markov models, when implemented as Prediction Suffix Trees [RST96] using the MDL principle. By applying a model clustering procedure, based on rate distortion theory combined with deterministic annealing, we obtain a hierarchical segmentation of sequences between alternating Markov sources. The method is applied successfully to unsupervised segmentation of multilingual texts into languages where it is able to infer correctly both the number of languages and the language switching points. When applied to protein sequence families (results of the [BSMT01] work), we demonstrate the method‘s ability to identify biologically meaningful sub-sequences within the proteins, which correspond to signatures of important functional sub-units called domains. Our approach to proteins classification (through the obtained signatures) is shown to have both conceptual and practical advantages over the currently used methods.

ei

PDF Web [BibTex]

PDF Web [BibTex]


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The control structure of artificial creatures

Zhou, D., Dai, R.

Artificial Life and Robotics, 5(3), 2001, invited article (article)

ei

Web [BibTex]

Web [BibTex]


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Support Vector Regression for Black-Box System Identification

Gretton, A., Doucet, A., Herbrich, R., Rayner, P., Schölkopf, B.

In 11th IEEE Workshop on Statistical Signal Processing, pages: 341-344, IEEE Signal Processing Society, Piscataway, NY, USA, 11th IEEE Workshop on Statistical Signal Processing, 2001 (inproceedings)

Abstract
In this paper, we demonstrate the use of support vector regression (SVR) techniques for black-box system identification. These methods derive from statistical learning theory, and are of great theoretical and practical interest. We briefly describe the theory underpinning SVR, and compare support vector methods with other approaches using radial basis networks. Finally, we apply SVR to modeling the behaviour of a hydraulic robot arm, and show that SVR improves on previously published results.

ei

PostScript [BibTex]

PostScript [BibTex]


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Markovian domain fingerprinting: statistical segmentation of protein sequences

Bejerano, G., Seldin, Y., Margalit, H., Tishby, N.

Bioinformatics, 17(10):927-934, 2001 (article)

ei

PDF Web [BibTex]

PDF Web [BibTex]


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Unsupervised Sequence Segmentation by a Mixture of Switching Variable Memory Markov Sources

Seldin, Y., Bejerano, G., Tishby, N.

In In the proceeding of the 18th International Conference on Machine Learning (ICML 2001), pages: 513-520, 18th International Conference on Machine Learning (ICML), 2001 (inproceedings)

Abstract
We present a novel information theoretic algorithm for unsupervised segmentation of sequences into alternating Variable Memory Markov sources. The algorithm is based on competitive learning between Markov models, when implemented as Prediction Suffix Trees (Ron et al., 1996) using the MDL principle. By applying a model clustering procedure, based on rate distortion theory combined with deterministic annealing, we obtain a hierarchical segmentation of sequences between alternating Markov sources. The algorithm seems to be self regulated and automatically avoids over segmentation. The method is applied successfully to unsupervised segmentation of multilingual texts into languages where it is able to infer correctly both the number of languages and the language switching points. When applied to protein sequence families, we demonstrate the method‘s ability to identify biologically meaningful sub-sequences within the proteins, which correspond to important functional sub-units called domains.

ei

PDF [BibTex]

PDF [BibTex]


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Kernel Machine Based Learning for Multi-View Face Detection and Pose Estimation

Cheng, Y., Fu, Q., Gu, L., Li, S., Schölkopf, B., Zhang, H.

In Proceedings Computer Vision, 2001, Vol. 2, pages: 674-679, IEEE Computer Society, 8th International Conference on Computer Vision (ICCV), 2001 (inproceedings)

ei

DOI [BibTex]

DOI [BibTex]


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Isotropic second-order nonlinear optical susceptibilities

Fischer, P., Buckingham, A., Albrecht, A.

PHYSICAL REVIEW A, 64(5), 2001 (article)

Abstract
The second-order nonlinear optical susceptibility, in the electric dipole approximation, is only nonvanishing for materials that are noncentrosymmetric. Should the medium be isotropic, then only a chiral system. such as an optically active liquid, satisfies this symmetry requirement. We derive the quantum-mechanical form of the isotropic component of the sum- and difference-frequency susceptibility and discuss its unusual spectral properties. We show that any coherent second-order nonlinear optical process in a system of randomly oriented molecules requires the medium to be chiral. and the incident frequencies to be different and nonzero. Furthermore, a minimum of two nondegenerate excited molecular states are needed for the isotropic part of the susceptibility to be nonvanishing. The rotationally invariant susceptibility is zero in the static field limit and shows exceptionally sensitive resonance and dephasing effects that are particular to chiral centers.

pf

DOI [BibTex]

DOI [BibTex]


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Reply to “Comment on ‘Phenomenological damping in optical response tensors’”

Buckingham, A., Fischer, P.

PHYSICAL REVIEW A, 63(4), 2001 (article)

Abstract
We show that damping factors must not be incorporated in the perturbation of the ground state by a static electric field. If they are included, as in the theory of Stedman et al. {[}preceding Comment. Phys. Rev. A 63, 047801 (2001)], then there would be an electric dipole in the y direction induced in a hydrogen atom in the M-s = + 1/2 state by a static electric field in the x direction. Such a dipole is excluded by symmetry.

pf

DOI [BibTex]


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Robust principal component analysis for computer vision

De la Torre, F., Black, M. J.

In Int. Conf. on Computer Vision, ICCV-2001, II, pages: 362-369, Vancouver, BC, USA, 2001 (inproceedings)

ps

pdf Project Page [BibTex]

pdf Project Page [BibTex]


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Learning image statistics for Bayesian tracking

Sidenbladh, H., Black, M. J.

In Int. Conf. on Computer Vision, ICCV-2001, II, pages: 709-716, Vancouver, BC, USA, 2001 (inproceedings)

ps

pdf [BibTex]

pdf [BibTex]


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Survey of nanomanipulation systems

Sitti, M.

In Nanotechnology, 2001. IEEE-NANO 2001. Proceedings of the 2001 1st IEEE Conference on, pages: 75-80, 2001 (inproceedings)

pi

[BibTex]

[BibTex]


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Nanotribological characterization system by AFM based controlled pushing

Sitti, M.

In Nanotechnology, 2001. IEEE-NANO 2001. Proceedings of the 2001 1st IEEE Conference on, pages: 99-104, 2001 (inproceedings)

pi

[BibTex]

[BibTex]


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Humanoid oculomotor control based on concepts of computational neuroscience

Shibata, T., Vijayakumar, S., Conradt, J., Schaal, S.

In Humanoids2001, Second IEEE-RAS International Conference on Humanoid Robots, 2001, clmc (inproceedings)

Abstract
Oculomotor control in a humanoid robot faces similar problems as biological oculomotor systems, i.e., the stabilization of gaze in face of unknown perturbations of the body, selective attention, the complexity of stereo vision and dealing with large information processing delays. In this paper, we suggest control circuits to realize three of the most basic oculomotor behaviors - the vestibulo-ocular and optokinetic reflex (VOR-OKR) for gaze stabilization, smooth pursuit for tracking moving objects, and saccades for overt visual attention. Each of these behaviors was derived from inspirations from computational neuroscience, which proves to be a viable strategy to explore novel control mechanisms for humanoid robotics. Our implementations on a humanoid robot demonstrate good performance of the oculomotor behaviors that appears natural and human-like.

am

link (url) [BibTex]

link (url) [BibTex]


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The coercivity of the melt-spun Sm-Fe-Ga-C permanent magnets and the effect of additives (Nb, Cu and Zr)

Zhang, J. X., Kleinschroth, I., Goll, D., Cuevas, F., Kronmüller, H.

{Journal of Physics-Condensed Matter}, 13(46):10487-10496, 2001 (article)

mms

[BibTex]

[BibTex]


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Hardness-depth profile of a carbon-implanted Ti-6Al-4V alloy and its relation to composition and microstructure

Kunert, M., Kienzle, O., Baretzky, B., Baker, S. P., Mittemeijer, E. J.

{Journal of Materials Research}, 16(8):2321-2335, 2001 (article)

mms

[BibTex]

[BibTex]


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New Sm(Co, Fe, Cu, Zr)(z) magnets with better temperature stability

Tang, W., Zhang, Y., Goll, D., Hadjipanayis, G. C., Kronmüller, H.

{Journal of Magnetism and Magnetic Materials}, 226(Sp. Iss. SI):1365-1366, 2001 (article)

mms

[BibTex]

[BibTex]


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Hydrogen in nanostructured vanadium-hydrogen systems

Orimo, S., Kimmerle, F., Majer, G.

{Physical Review B}, 63(9), 2001 (article)

mms

[BibTex]

[BibTex]


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Diffusion of hydrogen in heterogeneous systems

Herrmann, A., Schimmele, L., Mössinger, J., Hirscher, M., Kronmüller, H.

{Applied Physics A-Materials Science \& Processing}, 72(2):197-208, 2001 (article)

mms

[BibTex]

[BibTex]


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Computational micromagnetism of magnetic structures and magnetization processes in thin plantelets and small particles

Kronmüller, H., Hertel, R.

In Magnetic Storage Sstems Beyond 2000, 41, pages: 345-362, Nato Science Series II: Mathematics, Physics and Chemistry, Kluwer Academic Publishers, Rhodos, Greece, 2001 (inproceedings)

mms

[BibTex]

[BibTex]


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Structural vacancies in B2-CoAl and NiAl

Meyer, B., Bester, G., Fähnle, M.

{Scripta Materialia}, 44, pages: 2485-2488, 2001 (article)

mms

[BibTex]

[BibTex]


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Grain boundary phase transition in the Cu-Bi system

Straumal, B. B., Prokofyev, S. I., Chang, L.-S., Sluchanko, N. E., Baretzky, B., Gust, W., Mittemeijer, E. J.

{Diffusion and Defect Forum}, 194-199, pages: 1343-1348, 2001 (article)

mms

[BibTex]

[BibTex]


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Hydrogen storage in mechanically treated single wall carbon nanotrubes

Haluska, M., Hulman, M., Hirscher, M., Becher, M., Roth, S., Stepanek, I., Bernier, P.

In Electronic Properties of Molecular Nanostructures: XV International Winterschool/Euroconference, 591, pages: 603-608, American Institute of Physics Conference Proceedings, AIP, Kirchberg [Austria], 2001 (inproceedings)

mms

[BibTex]

[BibTex]


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Isotopic mass and lattice constant of Si and Ge: X-Ray standing wave measurements

Zegenhagen, J., Kazimirov, A., Cao, L. X., Konuma, M., Sozontov, E., Plachke, D., Carstanjen, H. D., Bilger, G., Haller, E., Kohn, V., Cardona, M.

In Proceedings of the 25th Conference on the Physics of Semiconductors, 87, pages: 125-127, Springer proceedings in physics, Springer, Osaka, Japan, 2001 (inproceedings)

mms

[BibTex]

[BibTex]


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Positron Annihilation Studies on Stable and Undercooled Metal Melts at the Stuttgart Pelletron

Stoll, H., Siegle, A., Major, J.

In Application of Accelerators in Research and Industry, 576, pages: 749-752, AIP Conference Proceedings, Denton, Texas, USA, 2001 (inproceedings)

mms

[BibTex]

[BibTex]


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Carbon nanostructures: an efficient hydrogen storage medium for fuel cells

Atkinson, K., Roth, S., Hirscher, M., Grünwald, W.

{Fuel Cells Bulletin}, 4(38):9-12, 2001 (article)

mms

[BibTex]

[BibTex]


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Magnetic domains in nanostructured media studied with M-TXM

Fischer, P., Eimüller, T., Schütz, G., Bayreuther, G., Tsunashima, S., Tagaki, N., Denbeaux, G., Attwood, D.

{Journal of Synchrotron Radiation}, 8, pages: 325-327, 2001 (article)

mms

[BibTex]

[BibTex]


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Compound formation and abrasion resistance of ion-implanted Ti6Al4V

Schmidt, H., Schminke, A., Schmiedgen, M., Baretzky, B.

{Acta Materialia}, 49, pages: 487-495, 2001 (article)

mms

[BibTex]

[BibTex]


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Towards flapping wing control for a micromechanical flying insect

Yan, J., Wood, R. J., Avadhanula, S., Sitti, M., Fearing, R. S.

In Robotics and Automation, 2001. Proceedings 2001 ICRA. IEEE International Conference on, 4, pages: 3901-3908, 2001 (inproceedings)

pi

[BibTex]

[BibTex]


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Man-machine interface for micro/nano manipulation with an afm probe

Aruk, B., Hashimoto, H., Sitti, M.

In Nanotechnology, 2001. IEEE-NANO 2001. Proceedings of the 2001 1st IEEE Conference on, pages: 151-156, 2001 (inproceedings)

pi

[BibTex]

[BibTex]


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Trajectory formation for imitation with nonlinear dynamical systems

Ijspeert, A., Nakanishi, J., Schaal, S.

In IEEE International Conference on Intelligent Robots and Systems (IROS 2001), pages: 752-757, Weilea, Hawaii, Oct.29-Nov.3, 2001, clmc (inproceedings)

Abstract
This article explores a new approach to learning by imitation and trajectory formation by representing movements as mixtures of nonlinear differential equations with well-defined attractor dynamics. An observed movement is approximated by finding a best fit of the mixture model to its data by a recursive least squares regression technique. In contrast to non-autonomous movement representations like splines, the resultant movement plan remains an autonomous set of nonlinear differential equations that forms a control policy which is robust to strong external perturbations and that can be modified by additional perceptual variables. This movement policy remains the same for a given target, regardless of the initial conditions, and can easily be re-used for new targets. We evaluate the trajectory formation system (TFS) in the context of a humanoid robot simulation that is part of the Virtual Trainer (VT) project, which aims at supervising rehabilitation exercises in stroke-patients. A typical rehabilitation exercise was collected with a Sarcos Sensuit, a device to record joint angular movement from human subjects, and approximated and reproduced with our imitation techniques. Our results demonstrate that multi-joint human movements can be encoded successfully, and that this system allows robust modifications of the movement policy through external variables.

am

link (url) [BibTex]

link (url) [BibTex]


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Real-time statistical learning for robotics and human augmentation

Schaal, S., Vijayakumar, S., D’Souza, A., Ijspeert, A., Nakanishi, J.

In International Symposium on Robotics Research, (Editors: Jarvis, R. A.;Zelinsky, A.), Lorne, Victoria, Austrialia Nov.9-12, 2001, clmc (inproceedings)

Abstract
Real-time modeling of complex nonlinear dynamic processes has become increasingly important in various areas of robotics and human augmentation. To address such problems, we have been developing special statistical learning methods that meet the demands of on-line learning, in particular the need for low computational complexity, rapid learning, and scalability to high-dimensional spaces. In this paper, we introduce a novel algorithm that possesses all the necessary properties by combining methods from probabilistic and nonparametric learning. We demonstrate the applicability of our methods for three different applications in humanoid robotics, i.e., the on-line learning of a full-body inverse dynamics model, an inverse kinematics model, and imitation learning. The latter application will also introduce a novel method to shape attractor landscapes of dynamical system by means of statis-tical learning.

am

link (url) [BibTex]

link (url) [BibTex]


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Interpretation of ab initio total energy results in a chemical language: I. Formalism and implementation into a mixed-basis pseudopotential code

Bester, G., Fähnle, M.

{Journal of Physics-Condensed Matter}, 13(50):11541-11550, 2001 (article)

mms

[BibTex]

[BibTex]


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Faceting of \sum3 and \sum9 grain boundaries in copper

Straumal, B. B., Polyakov, S. A., Bischoff, E., Gust, W., Mittemeijer, E. J.

{Interface Science}, 9(3-4):287-292, 2001 (article)

mms

[BibTex]

[BibTex]


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Generation and application of ultra-high-intensity magnetic field gradient pulses for NMR spectroscopy

Galvosas, P., Stallmach, F., Seiffert, G., Karger, J., Kaess, U., Majer, G.

{Journal of Magnetic Resonance}, 151(2):260-268, 2001 (article)

mms

[BibTex]

[BibTex]


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Formation and structure of highly over-stoichiometric LaNi5+x (x\textasciitilde1) alloys obtained by manifold non-equilibrium methods

Cuevas, F., Latroche, M., Hirscher, M., Percheron-Guegan, A.

{Journal of Alloys and Compounds}, 323, pages: 4-7, 2001 (article)

mms

[BibTex]

[BibTex]


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Hydrogen permeability measurement through Pd, Ni and Fe membranes

Yamakawa, K., Ege, M., Ludescher, B., Hirscher, M., Kronmüller, H.

{Journal of Alloys and Compounds}, 321(1):17-23, 2001 (article)

mms

[BibTex]

[BibTex]


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Ab-initio statistical mechanics for the phase diagram of NiAl including the effect of vacancies

Lechermann, F., Fähnle, M.

{Physica Status Solidi B-Basic Research}, 224(2):R4-R6, 2001 (article)

mms

[BibTex]

[BibTex]