Neural control of movement is typically studied in constrained environments where there is a reduced set of possible behaviors. This constraint may unintentionally limit the applicability of findings to the generalize...
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Neural control of movement is typically studied in constrained environments where there is a reduced set of possible behaviors. This constraint may unintentionally limit the applicability of findings to the generalized case of unconstrained behavior. We hypothesize that examining the unconstrained state across multiple behavioral contexts will lead to new insights into the neural control of movement and help advance the design of neural prosthetic decode algorithms. However, to pursue electrophysiological studies in such a manner requires a more flexible framework for experimentation. We propose that head-mounted neural recording systems with wireless data transmission, combined with markerless computer-vision based motion tracking, will enable new, less constrained experiments. As a proof-of-concept, we recorded and wirelessly transmitted broadband neural data from 32 electrodes in premotor cortex while acquiring single-camera video of a rhesus macaque walking on a treadmill. We demonstrate the ability to extract behavioral kinematics using an automated computer vision algorithm without use of markers and to predict kinematics from the neural data. Together these advances suggest that a new class of “freely moving monkey” experiments should be possible and should help broaden our understanding of the neural control of movement.
We present a novel development of a domain decomposition method for the Navier-Stokes equations in a spectral element formulation which enables to investigate turbulent flows in complex geometries. The current paper a...
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The idea of a Kripke semantics endowed with possibility/plausibility information is not new; in fact there are different approaches for that; see: [6], [13], [16], [19]. This paper follows the approach found in [6], b...
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The idea of a Kripke semantics endowed with possibility/plausibility information is not new; in fact there are different approaches for that; see: [6], [13], [16], [19]. This paper follows the approach found in [6], but whereas [6] provides a fixed interpretation for connectives into [0,1] here we provide a characterization of a fuzzy semantics for connectives in such a way that the resulting fuzzy frames: K, T and D, are described precisely by the set of statements which also describes, respectively, the usual modal systems K, T and D.
Consider piece-wise constant approximations to a function of several parameters, and the problem of finding the best such approximation from measurements at a set of points in the parameter space. We find good approxi...
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This paper presents a novel approach to networked control systems (NCS) analysis and design that provides increased control performance for a set of control loops that exchange control data over the Controller Area Ne...
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The problem of model selection arises in a number of contexts, such as subset selection in linear regression, estimation of structures in graphical models, and signal denoising. This paper studies non-asymptotic model...
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The problem of model selection arises in a number of contexts, such as subset selection in linear regression, estimation of structures in graphical models, and signal denoising. This paper studies non-asymptotic model selection for the general case of arbitrary (random or deterministic) design matrices and arbitrary nonzero entries of the signal. In this regard, it generalizes the notion of incoherence in the existing literature on model selection and introduces two fundamental measures of coherence- termed as the worst-case coherence and the average coherence-among the columns of a design matrix. It utilizes these two measures of coherence to provide an in-depth analysis of a simple, model-order agnostic one-step thresholding (OST) algorithm for model selection and proves that OST is feasible for exact as well as partial model selection as long as the design matrix obeys an easily verifiable property, which is termed as the coherence property. One of the key insights offered by the ensuing analysis in this regard is that OST can successfully carry out model selection even when methods based on convex optimization such as the lasso fail due to the rank deficiency of the submatrices of the design matrix. In addition, the paper establishes that if the design matrix has reasonably small worst-case and average coherence then OST performs near-optimally when either (i) the energy of any nonzero entry of the signal is close to the average signal energy per nonzero entry or (ii) the signal-to-noise ratio in the measurement system is not too high. Finally, two other key contributions of the paper are that (i) it provides bounds on the average coherence of Gaussian matrices and Gabor frames, and (ii) it extends the results on model selection using OST to low-complexity, model-order agnostic recovery of sparse signals with arbitrary nonzero entries. In particular, this part of the analysis in the paper implies that an Alltop Gabor frame together with OST can successfully carr
We define a new "contour person" model of the human body that has the expressive power of a detailed 3D model and the computational benefits of a simple 2D part-based model. The contour person (CP) model is ...
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ISBN:
(纸本)9781424469840;9781424469857
We define a new "contour person" model of the human body that has the expressive power of a detailed 3D model and the computational benefits of a simple 2D part-based model. The contour person (CP) model is learned from a 3D SCAPE model of the human body that captures natural shape and pose variations;the projected contours of this model, along with their segmentation into parts forms the training set. The CP model factors deformations of the body into three components: shape variation, viewpoint change and part rotation. This latter model also incorporates a learned non-rigid deformation model. The result is a 2D articulated model that is compact to represent, simple to compute with and more expressive than previous models. We demonstrate the value of such a model in 2D pose estimation and segmentation. Given an initial pose from a standard pictorial-structures method, we refine the pose and shape using an objective function that segments the scene into foreground and background regions. The result is a parametric, human-specific, image segmentation.
Common restoration techniques use a single observed image for the processing. In this work three observed degraded images obtained from camera microscanning are utilized for image restoration. It is assumed that the d...
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The Controller Area Network (CAN) provides the basis for many cost-effective distributed embedded systems. In this paper, we present a novel approach to networked control systems (NCS) analysis and design that provide...
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In this paper, a large scale Medium Voltage DC all-electric ship integrated power system is modeled from the prime mover (gas turbine) to the propulsion load. This system has a three-phase 21MW synchronous machine as ...
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ISBN:
(纸本)9781617387043
In this paper, a large scale Medium Voltage DC all-electric ship integrated power system is modeled from the prime mover (gas turbine) to the propulsion load. This system has a three-phase 21MW synchronous machine as a main generator and a three-phase 19MW induction motor as a main propulsion drive. The influence of propeller emergence on both electrical and mechanical components of the system is investigated.
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