Data-driven and Model-based Verification: a Bayesian Identification Approach

This work develops a measurement-driven and model-based formal verification approach, applicable to systems with partly unknown dynamics. We provide a principled method, grounded on reachability analysis and on Bayesian inference, to compute the confidence that a physical system driven by external inputs and accessed under noisy measurements, verifies a temporal logic property. A case study is discussed, where we investigate the bounded- and unbounded-time safety of a partly unknown linear time invariant system

Observer-based correct-by-design controller synthesis

Current state-of-the-art correct-by-design controllers are designed for full-state measurable systems. This work first extends the applicability of correct-by-design controllers to partially observable LTI systems. Leveraging 2nd order bounds we give a design method that has a quantifiable robustness to probabilistic disturbances on state transitions and on output measurements. In a case study from smart buildings we evaluate the new output-based correct-by-design controller on a physical system with limited sensor information

Gate Oxide Reliability and Deuterated CMOS Processing

In recent literature, a controversy has arisen over the question whether deuterium improves the stability of the MOS gate dielectric. It appears as if this controversy finds its origin in the different stages (e.g. oxidation or post metal anneal) deuterium is introduced in the CMOS process. This paper investigates this in detail. The obtained results show that the hot carrier degradation only benefits from an isotope effect when deuterium is introduced in the post metal anneal. At the same time, charge to breakdown for high quality oxides does not benefit from an isotope effect, regardless of the processing stage deuterium is introduced, or the gate oxide thickness used. This is verified on two different sets of wafers fabricated in two different laboratories

Prediction error identification of linear dynamic networks with rank-reduced noise

Dynamic networks are interconnected dynamic systems with measured node signals and dynamic modules reflecting the links between the nodes. We address the problem of \red{identifying a dynamic network with known topology, on the basis of measured signals}, for the situation of additive process noise on the node signals that is spatially correlated and that is allowed to have a spectral density that is singular. A prediction error approach is followed in which all node signals in the network are jointly predicted. The resulting joint-direct identification method, generalizes the classical direct method for closed-loop identification to handle situations of mutually correlated noise on inputs and outputs. When applied to general dynamic networks with rank-reduced noise, it appears that the natural identification criterion becomes a weighted LS criterion that is subject to a constraint. This constrained criterion is shown to lead to maximum likelihood estimates of the dynamic network and therefore to minimum variance properties, reaching the Cramer-Rao lower bound in the case of Gaussian noise.Comment: 17 pages, 5 figures, revision submitted for publication in Automatica, 4 April 201

The Impact of Deuterated CMOS processing on Gate Oxide Reliability

In recent literature, a controversy has arisen over the question whether deuterium improves the stability of the MOS gate dielectric. In particular, the influence of deuterium incorporation on the bulk oxide quality is not clear. In this letter, deuterium or hydrogen is introduced during either the gate oxidation, postoxidation anneal, and/or the postmetal anneal (PMA). The oxide bulk degradation was evaluated using charge-to-breakdown and stress-induced leakage current; and the oxide interface degradation using hot-carrier degradation and low-frequency noise. The obtained results show that the oxide bulk does not benefit from the presence of deuterium, regardless of the stage of deuterium introduction, or the gate oxide thickness. The oxide interface is more stable only when deuterium is introduced in the PMA

Local module identification in dynamic networks with correlated noise: the full input case

The identification of local modules in dynamic networks with known topology has recently been addressed by formulating conditions for arriving at consistent estimates of the module dynamics, typically under the assumption of having disturbances that are uncorrelated over the different nodes. The conditions typically reflect the selection of a set of node signals that are taken as predictor inputs in a MISO identification setup. In this paper an extension is made to arrive at an identification setup for the situation that process noises on the different node signals can be correlated with each other. In this situation the local module may need to be embedded in a MIMO identification setup for arriving at a consistent estimate with maximum likelihood properties. This requires the proper treatment of confounding variables. The result is an algorithm that, based on the given network topology and disturbance correlation structure, selects an appropriate set of node signals as predictor inputs and outputs in a MISO or MIMO identification setup. As a first step in the analysis, we restrict attention to the (slightly conservative) situation where the selected output node signals are predicted based on all of their in-neighbor node signals in the network.Comment: Extended version of paper submitted to the 58th IEEE Conf. Decision and Control, Nice, 201

Three-dimensional retinal image stability during visual tilt discrimination in the rabbit

Abstract Rabbits trained to discriminate vertical vs. oblique striations are unable to discriminate angular differences of 5°. In the present study the instabilities around the roll axis of the eyes were measured during visual discrimination. The results indicate that these instabilities are one of the causes of the rabbit's inability to discriminate angular differences of 5°