A robust deconvolution scheme for fault detection and isolation of uncertain linear systems: an LMI approach

Optimal H_∞ deconvolution filter theory is exploited for the design of robust fault detection and isolation (FDI) units for uncertain polytopic linear systems. Such a filter is synthesized under frequency domain conditions which ensure guaranteed levels of disturbance attenuation, residual decoupling and deconvolution performance in prescribed frequency ranges. By means of the Projection Lemma, a quasi-convex formulation of the problem is obtained via LMIs. A FDI logic based on adaptive thresholds is also proposed for reducing the generation of false alarms. The effectiveness of the design technique is illustrated via a numerical example.     

Rational Unification in 28 Characters

We present a case study where Synchronising Graphs, a system of parallel graph transformation, are used to solve the syntactic unification problem for first order rational terms (with possibly infinite unifier). The solution we offer is efficient, that is quasi-linear, and simple: a program of 28 characters.     

Characterization of transient currents in HfO2 capacitors in the short timescale

We present a detailed experimental investigation of transient currents in HfO₂ capacitors in the short timescale. We show that the transient currents flowing through the capacitor plates when the gate voltage is reset to zero after a low voltage stress period follow a power-law time dependence t^−α (with α ? 1) over more than eight decades of time and down to the μs timescale. As transient currents in HfO₂ are largely increased with respect to the SiO₂ case, these results confirm that transient effects can be a severe issue for the successful integration of high-k dielectrics.     

Reasoning on temporal class diagrams: Undecidability results

This paper introduces a temporal class diagram language useful to model temporal varying data. The atemporal portion of the language contains the core constructors available in both EER diagrams and UML class diagrams. The temporal part of the language is able to distinguish between temporal and atemporal constructs, and it has the ability to represent dynamic constraints between classes. The language is characterized by a model-theoretic (temporal) semantics. Reasoning services as logical implication and satisfiability are also defined. We show that reasoning on finite models is different from reasoning on unrestricted ones. Then, we prove that reasoning on temporal class diagrams is an undecidable problem on both unrestricted models and on finite ones.     

Construction of discrete-time models for port-controlled Hamiltonian systems with applications

The issues of constructing a discrete-time model for Hamiltonian systems are in general different from those for dissipative systems. We propose an algorithm for constructing an approximate discrete-time model, which guarantees Hamiltonian conservation. We show that the algorithm also preserves, in a weaker sense, the losslessness property of a class of port-controlled Hamiltonian systems. An application of the algorithm to port-controlled Hamiltonian systems with quadratic Hamiltonian is presented, and we use this to solve the stabilization problem for this class of systems based on the approximate discrete-time model constructed using the proposed algorithm. We illustrate the usefulness of the algorithm in designing a discrete-time controller to stabilize the angular velocity of the dynamics of a rigid body.     

Using 3D Sound to Improve the Effectiveness of the Advanced Driver Assistance Systems

Future generation cars will be characterized by a wide range of Information Technology (IT) services providing safety and infotainment. This makes the car an information intensive environment where the visual channel is overloaded, putting the safety of drivers and passengers in jeopardy. We propose the use of a 3D auditory display to provide information from the Advanced Driver Assistance Systems. This reduces the eye-off-road time, exploiting the human capability to associate sounds with positions in space. Preliminary lab tests reveal the suitability of this approach. The system still has to be carefully tuned and personalized to achieve usability and reliability, but we think that it provides a complementary channel that is specially useful in low visibility conditions.     

Practical L2 disturbance attenuation for nonlinear systems

In this work, a notion of generalized L₂-gain for nonlinear systems, where the gain is considered as a function of the state instead of a (global) constant, is presented. This new notion seems to be adequate to characterize the gain properties of several nonlinear systems which do not possess a uniform L₂-gain property (i.e. the L₂-gain depends on the operating point). Moreover, a notion of practical L₂-gain attenuation, which extends the standard definition and parallels (mutatae mutandis) the concepts of practical stability, is also proposed.     

A survey on off-line Cursive Word Recognition

This paper presents a survey on off-line Cursive Word Recognition. The approaches to the problem are described in detail. Each step of the process leading from raw data to the final result is analyzed. This survey is divided into two parts, the first one dealing with the general aspects of Cursive Word Recognition, the second one focusing on the applications presented in the literature.     

Optimal Structure from Motion: Local Ambiguities and Global Estimates

Structure From Motion (SFM) refers to the problem of estimating spatial properties of a three-dimensional scene from the motion of its projection onto a two-dimensional surface, such as the retina. We present an analysis of SFM which results in algorithms that are provably convergent and provably optimal with respect to a chosen norm.In particular, we cast SFM as the minimization of a high-dimensional quadratic cost function, and show how it is possible to reduce it to the minimization of a two-dimensional function whose stationary points are in one-to-one correspondence with those of the original cost function. As a consequence, we can plot the reduced cost function and characterize the configurations of structure and motion that result in local minima. As an example, we discuss two local minima that are associated with well-known visual illusions. Knowledge of the topology of the residual in the presence of such local minima allows us to formulate minimization algorithms that, in addition to provably converge to stationary points of the original cost function, can switch between different local extrema in order to converge to the global minimum, under suitable conditions. We also offer an experimental study of the distribution of the estimation error in the presence of noise in the measurements, and characterize the sensitivity of the algorithm using the structure of Fisher's Information matrix.