32,932 research outputs found
Maximum Hands-Off Control: A Paradigm of Control Effort Minimization
In this paper, we propose a new paradigm of control, called a maximum
hands-off control. A hands-off control is defined as a control that has a short
support per unit time. The maximum hands-off control is the minimum support (or
sparsest) per unit time among all controls that achieve control objectives. For
finite horizon control, we show the equivalence between the maximum hands-off
control and L1-optimal control under a uniqueness assumption called normality.
This result rationalizes the use of L1 optimality in computing a maximum
hands-off control. We also propose an L1/L2-optimal control to obtain a smooth
hands-off control. Furthermore, we give a self-triggered feedback control
algorithm for linear time-invariant systems, which achieves a given sparsity
rate and practical stability in the case of plant disturbances. An example is
included to illustrate the effectiveness of the proposed control.Comment: IEEE Transactions on Automatic Control, 2015 (to appear
Synergy-based Hand Pose Sensing: Reconstruction Enhancement
Low-cost sensing gloves for reconstruction posture provide measurements which
are limited under several regards. They are generated through an imperfectly
known model, are subject to noise, and may be less than the number of Degrees
of Freedom (DoFs) of the hand. Under these conditions, direct reconstruction of
the hand posture is an ill-posed problem, and performance can be very poor.
This paper examines the problem of estimating the posture of a human hand
using(low-cost) sensing gloves, and how to improve their performance by
exploiting the knowledge on how humans most frequently use their hands. To
increase the accuracy of pose reconstruction without modifying the glove
hardware - hence basically at no extra cost - we propose to collect, organize,
and exploit information on the probabilistic distribution of human hand poses
in common tasks. We discuss how a database of such an a priori information can
be built, represented in a hierarchy of correlation patterns or postural
synergies, and fused with glove data in a consistent way, so as to provide a
good hand pose reconstruction in spite of insufficient and inaccurate sensing
data. Simulations and experiments on a low-cost glove are reported which
demonstrate the effectiveness of the proposed techniques.Comment: Submitted to International Journal of Robotics Research (2012
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Exchange Rate Pegging: Credibility and Fundamentals. Evidence from Greece
The paper examines the predictability of a currency-peg collapse on the basis of the
movements of underlying fundamentals and the observed behaviour of currency
markets. Our findings suggest that the ultimate collapse of a peg is predictable if the
peg is inconsistent with valid long-run macroeconomic relationships. A strong
currency policy is confirmed to be helpful in terms of reducing inflation but its
prolonged implementation reduces the pegâs credibility. In the case-study examined,
markets appear to have anticipated the pegâs collapse almost a year before it occurred.
However, the results show that the exact timing of the devaluation took markets by
surprise. Even under conditions of devaluation expectations, central banks have the
capacity to surprise the markets
Feature extraction using extrema sampling of discrete derivatives for spike sorting in implantable upper-limb neural prostheses
Next generation neural interfaces for upper-limb (and other) prostheses aim to develop implantable interfaces for one or more nerves, each interface having many neural signal channels that work reliably in the stump without harming the nerves. To achieve real-time multi-channel processing it is important to integrate spike sorting on-chip to overcome limitations in transmission bandwidth. This requires computationally efficient algorithms for feature extraction and clustering suitable for low-power hardware implementation. This paper describes a new feature extraction method for real-time spike sorting based on extrema analysis (namely positive peaks and negative peaks) of spike shapes and their discrete derivatives at different frequency bands. Employing simulation across different datasets, the accuracy and computational complexity of the proposed method are assessed and compared with other methods. The average classification accuracy of the proposed method in conjunction with online sorting (O-Sort) is 91.6%, outperforming all the other methods tested with the O-Sort clustering algorithm. The proposed method offers a better tradeoff between classification error and computational complexity, making it a particularly strong choice for on-chip spike sorting
Claiming the Indomitable Wave: Masculinities, Sexualities, and the Realm of Surfing in Costa Rica
Examining the relationship between masculinity, sexuality, and the sport of surfing in the context of Costa Rica. Questions the nature of emergent counter identities in the hyper-masculine realm of the surfing subculture and the ways in which the emergence of counter identities changes the nature of the subculture. Focuses on the anthropology of sport, the anthropology of sexuality, and theories of territoriality
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