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Using smartphones for indoor motion trajectory tracing has attracted a lot of attention in recent years, which offers great potential to support a broad spectrum of applications in indoor environment, including elder care, business analysis, and navigation. Yet most existing approaches only work for certain pedestrian’s motion modes or smartphone’s carrying patterns, which lack the robustness and...
In this paper, a novel method is proposed to extract hand gesture features in real-time from RGB-D images captured by the Microsoft's Kinect. A contour length information based de-noise method is introduced for the hand gesture smooth segmentation and edge contour extraction. In addition, a finger earth mover's distance algorithm is applied with a novel approach to locate the palm image and extract...
Independent Component Analysis (ICA) algorithms taking advantage of the potential non-circular property of complex signals have been recently derived and shown to lead to improved performances. We investigate the performance of three ICA approaches to extract a weak co-channel interfering communications signal from a television broadcast signal over varied interference-to-noise ratios: complex maximization...
In this work, we introduce a method to do object extraction in RGBD images. Our method consists in a depth-based approach which provides an insight into connectedness, proximity and planarity of the scene. We combine the depth and the color in a GraphCut framework to achieve robustness. Specifically, we propose a depth-based seeding which reduces the uncertainty and limitations of the traditional...
Event-triggered and self-triggered control have recently been proposed as an alternative to periodic implementations of feedback control laws over sensor/actuator networks. In event-triggered control, each sensing node continuously monitors the plant in order to determine if fresh information should be transmitted and if the feedback control law should be recomputed. In general, event-triggered control...
Wireless sensor networks had a big diffusion in the last few decades and they are used in many application domains. Services built on them require to handle a big amount of data, and a fundamental requirement is their quality, highly affected by the security of the whole system. Some encryption techniques can be adopted, but it is also necessary to verify the reliability of nodes that sense, aggregate,...
In nature, many animals are able to jump, upright themselves after landing and jump again. This allows them to move in unstructured and rough terrain. As a further development of our previously presented 7 g jumping robot, we consider various mechanisms enabling it to recover and upright after landing and jump again. After a weighted evaluation of these different solutions, we present a spherical...
We consider the problem of spectrum sensing in cognitive radio networks. In our previous work we have developed DualCUSUM, a distributed algorithm for change detection and used it for cooperative spectrum sensing. The algorithm is based on sequential change detection techniques which optimally use the past observations. But DualCUSUM requires the knowledge of the channel gains for each of the secondary...
A key enabling functionality in implementing Cognitive Radio is to reliably detect the licensed users. In recent literature, cooperation among spectrum sensing terminals is suggested to offer reliable sensing performance. We consider the problem that the presence of malfunctioning or malicious sensing terminals will severely degrade the performance of cooperative spectrum sensing. In this paper, we...
Transitioning nanoscale devices from the realm of one-of-a-kind feats into robust and reproducible nanosystems - that is, useable technology - is a monumental challenge that transcends the capabilities of any one laboratory. Some solid progress is now being achieved toward this end, and these efforts are critical for realizing the promise of ldquoactiverdquo nanotechnology. At least two essential...
Compressive sensing (CS) is an alternative to Shannon/Nyquist sampling for acquiring sparse or compressible signals. Instead of taking N periodic samples, we measure M ?? N inner products with random vectors and then recover the signal via a sparsity-seeking optimization or greedy algorithm. A new framework for CS based on unions of subspaces can improve signal recovery by including dependencies between...
Achieving a robust recognition of physical activities or gestures despite variability in sensor placement is highly important for the real-world deployment of wearable context-aware systems.It provides robustness against unintentional displacement of sensors, such as when doing intense physical activities or wearing sensors over extended periods of time.Here we focus on the problem of context recognition...
Cognitive radios have the potential to greatly improve spectral efficiency in wireless networks. Cognitive radios are considered lower priority or secondary users of spectrum allocated to a primary user. Their fundamental requirement is to avoid interference to potential primary users in their vicinity. Spectrum sensing has been identified as a key enabling functionality to ensure that cognitive radios...
Wireless sensor networks (WSNs) play an important role in several application fields. They are composed by a dense deployment of small and low-power devices (called sensors) that cooperate together in order to perform some special tasks. These networks are often characterized by the spatial and temporal correlation of the sensor observations. Several works are investigating these correlations in order...
Positioning disk-shaped sensors to optimize certain coverage parameters is a fundamental problem in ad-hoc sensor networks. The hexagon grid lattice is known to be optimally efficient, but the 20.9% of the area covered by two sensors may be considered a waste. Furthermore, any movement of a sensor from its designated grid position or sensor failure, due to placement error or obstacle avoidance, leaves...
Accurate target localization is an important task in various commercial and military applications. One way to achieve this goal is to use the time-of-arrival (TOA) or time-delay-of-arrival (TDOA) information observed at multiple distributed sensors. On the other hand, there is a great need to use moving sensors to form a radar platform with synthetic apertures. In this paper, we consider the problem...
Compressive sensing (CS) is an alternative to Shannon/Nyquist sampling for acquisition of sparse or compressible signals; instead of taking periodic samples, we measure inner products with M < N random vectors and then recover the signal via a sparsity-seeking optimization or greedy algorithm. Initial research has shown that by leveraging stronger signal models than standard sparsity, the number...
This paper proposes a modified split and merge algorithm for line extraction with high accuracy, efficient speed and low complexity. It is robust against measurement noises and demonstrates satisfactory results on different surfaces in determining line boundaries. The method is based on the least square equation to fit a line on a series of uncertain points. Different least square criterion is investigated...
This paper is concerned with the robust Hinfin filtering problem for a class of uncertain nonlinear networked systems with both multiple stochastic time-varying communication delays and multiple packet dropouts. The discrete-time system under consideration is also subject to parameter uncertainties, state-dependent stochastic disturbances and sector-bounded nonlinearities. Sufficient conditions are...
The reliable Hinfin control problem for time-varying delayed discrete-time systems is proposed for the case of a simultaneous presence of sensor failures. A more practical general mode of sensor is presented to investigate sensor failures. Based on a linear matrix inequality (LMI) technique, an observer-based reliable controller is designed, such that, both in normal and fault cases of sensor, the...
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