1,721,440 research outputs found
A cellular nonlinear approach to decentralized locomotion control of the stick insect
No full textArena P, Cruse H, Fortuna L, Frasca M, Patané L. A cellular nonlinear approach to decentralized locomotion control of the stick insect. In: Proceedings 2002 IEEE International Symposium on Circuits and Systems. Piscataway, NJ: IEEE Operations Center; 2002: 165-168
Chaotic Pulse Position Modulation to Improve the Efficiency of Sonar Sensors
No full textUltrasonic devices are widely used in robotics as exteroceptive sensors for ranging measurements. Robotic applications often involve a large number of sonars operating concurrently, giving rise to the phenomenon of crosstalk. In this work, the problem of improving performance of ultrasonic devices in the presence of crosstalk and noise is addressed. In order for each device to discriminate its own echo, chaos is exploited to create unique firing sequences. In particular, the firing scheme described in this work is inspired to a modulation scheme used in chaotic communications, called chaotic pulse position modulation (CPPM). The evaluation of the time of flight is performed by a detection filter. The experimental setup consists of a Polaroid 600 electrostatic transducer driven by a continuous CPPM modulator. Experimental results confirm the suitability of the approach
Synchronization in Networks of Mobile Agents
No full textIn this Chapter we study synchronization issues in a system of mobile agents. Agents move as random walkers and interact with neighbouring units. Each agent carries a chaotic oscillator and coupling between oscillators occurs only when agents interact. Consequently, the interaction matrix is time-varying and appropriate synchronization criteria have to be defined
Interior W2,p estimates for non divergence elliptic equations with discontinuous coefficients
No full textIl classico risultato di Agmon-Douglis-Nirenberg viene esteso al caso dei coefficienti VM
W2p-solvability of the Dirichlet problem for nondivergence elliptic equations with VMO coefficients
No full textPrevious results on the Lp regularity in the interior are extended to the boundar
Reachability analysis in stochastic directed graphs by reinforcement learning
Full text linkWe characterize the reachability probabilities in stochastic directed graphs by means of reinforcement learning methods. In particular, we show that the dynamics of the transition probabilities in a stochastic digraph can be modeled via a difference inclusion, which, in turn, can be interpreted as a Markov decision process. Using the latter framework, we offer a methodology to design reward functions to provide upper and lower bounds on the reachability probabilities of a set of nodes for stochastic digraphs. The effectiveness of the proposed technique is demonstrated by application to the diffusion of epidemic diseases over time-varying contact networks generated by the proximity patterns of mobile agents
Are IoBT services accessible to everyone?
No full textBiometric recognition aims at identifying a person by using their physiological or behavioral characteristics. When adopted for improving the security in the Internet of Things (IoT) field, it is commonly named Internet of Biometric Things (IoBT). However, despite its advantages there are further considerations on security and different ethical and legal issues, such as the possibility of exclusion of individuals due to pathologies, injuries, disabilities, or genetic defects. Indeed, these specific physical condition would lead to not satisfy the requirements commonly used for biometric recognition. As a consequence, the limitations of current biometric systems can exclude a person from the use of IoBT services. In this paper, we focus on the difficulty of iris recognition when it is affected by Coloboma, a congenital abnormality of membranes of the eye. We show how this pathological state impacts on the performance of the Daugman and Canny edge detection algorithms, which represent the most widespread methods used for the iris localization step in eye-based biometric. Results of an experimentation revealed that they correctly detected only 15.79% and 47.37% of Coloboma iris, respectively. In order to avoid the use of these inaccurate algorithms in case of Coloboma eye, we designed and experimented a Residual Neural Network classifier able to detect the presence of this disease with 99.79% of accuracy. This classifier may be a first step towards a more sophisticated “diversity-aware” biometric system which represents an alternative to actual IoBT authentication method for people with special physical condition
Reachability analysis in stochastic directed graphs by reinforcement learning
No full textWe characterize the reachability probabilities in stochastic directed graphs by means of reinforcement learning methods. In particular, we show that the dynamics of the transition probabilities in a stochastic digraph can be modeled via a difference inclusion, which, in turn, can be interpreted as a Markov decision process. Using the latter framework, we offer a methodology to design reward functions to provide upper and lower bounds on the reachability probabilities of a set of nodes for stochastic digraphs. The effectiveness of the proposed technique is demonstrated by application to the diffusion of epidemic diseases over time-varying contact networks generated by the proximity patterns of mobile agents
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