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Analog and Mixed Signal (AMS) designs are an important part of embedded systems that link digital designs to the analog world. Due to challenges associated with its verification process, AMS designs require a considerable portion of the total design cycle time. In contrast to digital designs, the verification of AMS systems is a challenging task that requires lots of expertise and deep understanding of their behavior. Researchers started lately studying the applicability of formal methods for the verification of AMS systems as a way to tackle the limitations of conventional verification methods like simulation. This paper surveys research activities in the formal verification of AMS designs as well as compares the different proposed approaches.

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The potential for using computer vision techniques to solve several shortcomings associated with traditional road safety and behavior analysis is demonstrated. Surrogate data such as traffic conflicts provide invaluable information that can be used to understand collision-contributing factors and the collision failure mechanism better. Recent advances in computer vision techniques have encouraged the use of proactive safety surrogate measures such as detection of conflicts and violations. The objective of this study is to demonstrate the automated safety diagnosis of pedestrian crossing safety issues by using computer vision techniques. The automated safety diagnosis is applied at a major signalized intersection in downtown Vancouver, British Columbia, Canada, at which concerns had been raised regarding the high conflict rate between vehicles and pedestrians as well as the elevated number of traffic violations (i.e., jaywalking). This study is unique in its attempt to extract conflict indicators and detect violations from video sequences in a fully automated way. This line of research benefits safety experts because it provides a prompt and objective safety evaluation for intersections. The research also provides a permanent database for traffic information that can be beneficial for a sound safety diagnosis as well as for developing safety countermeasures.

We propose a new symbolic verification methodology for proving the properties of analog and mixed signal (AMS) designs. Starting with an AMS description and a set of properties and using symbolic computation, we extract a normal mathematical representation for the system in terms of recurrence equations. These normalized equations are used along with an induction verification strategy defined inside the computer algebra system Mathematica to prove the correctness of the properties. We apply our methodology on a third order ∆Σ modulator.

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