Bis zu 50 % günstiger als neu 3 Jahre rebuy Garantie Professionelles Refurbishment

Bordersearch: Efficient Characterization of Automotive Electronic Systems Through Machine Learning

Derzeit nicht verfügbar

Handgeprüfte Gebrauchtware

Bis zu 50 % günstiger als neu

Der Umwelt zuliebe

Bordersearch: Efficient Characterization of Automotive Electronic Systems Through Machine Learning

Markus Dobler (Taschenbuch, Englisch)

Keine Bewertungen vorhanden

Optischer Zustand

Beschreibung

The complexity of modern electrical and electronic systems increases steadily. In the automotive industry, this trend is amplified by current developments such as the growing number of advanced driver assistance systems and the emergence of electric drive vehicles. To guarantee their safety and reliability, chips and devices have to be verified thoroughly and comprehensively. This requirement is reinforced by new regulations such as ISO 26262. As a consequence, for characterization and verification, chips and devices are now often tested within their application context. However, this drastically increases the number of parameters that have to be considered when investigating the reason of possible failure. Established characterization and verification methodologies only work well with a limited number of parameters, as they otherwise would have to perform an infeasible amount of tests to provide reliable results. Therefore, new methodologies are required that can efficiently handle systems which have dozens of parameters. To overcome this problem, this thesis presents a new methodology, termed Bordersearch, which analyzes systems based on functional tests that only provide binary responses, i.e. “pass” or “fail”. Internally, it combines several machine learning techniques, which allow it to operate efficiently and reliably on systems with dozens of parameters: A classifier robustly predicts the border between pass and fail region; additionally, it estimates how certain that prediction is in different regions of the parameter space. Based on that information, an adaptive sampling strategy concentrates most tests close to the border. Thus, each test provides much information about the border, and even with comparatively few samples, Bordersearch can accurately resolve the border. Additionally, Bordersearch performs an automated detection of relevant parameters and provides novel ways to visualize the multi-dimensional interaction between them. With this assistance, the results of an experiment can easily be understood and interpreted without a deep knowledge of machine learning and statistics. Bordersearch has been applied successfully for the characterization of several automotive systems. In all these experiments, it was consistently faster and more accurate than state-of-the-art methods. It is thus a vital contribution to the efforts that enhance the verification of e/e systems to keep pace with other advancements in the automotive industry. Weniger zeigen

Dieses Produkt haben wir gerade leider nicht auf Lager.

ab 36,99 €

Derzeit nicht verfügbar

Handgeprüfte Gebrauchtware

Bis zu 50 % günstiger als neu

Der Umwelt zuliebe

Produktinformationen

Technische Daten

Erscheinungsdatum

01.09.2018

Sprache

Englisch

EAN

9783843937054

Herausgeber

Dr. Hut

Serien- oder Bandtitel

Informatik

Sonderedition

Nein

Autor

Markus Dobler

Seitenanzahl

142

Einbandart

Taschenbuch

Schlagwörter

Machine Learning, Characterization, Automotive Electronic Systems

Thema-Inhalt

U - EDV und Informationstechnologie UY - Informatik

Höhe

210 mm

Breite

14.8 cm

Warnhinweise und Sicherheitsinformationen

Informationen nach EU Data Act

Bewertungen

-.-

Leider noch keine Bewertungen

Sicher bei rebuy kaufen

Sehr Gut, 4.52/5.00

Aus 200.000+ Bewertungen

Schreib die erste Bewertung für dieses Produkt!

Wenn du eine Bewertung für dieses Produkt schreibst, hilfst du allen Kund:innen, die noch überlegen, ob sie das Produkt kaufen wollen. Vielen Dank, dass du mitmachst!