Standaard Boekhandel gebruikt cookies en gelijkaardige technologieën om de website goed te laten werken en je een betere surfervaring te bezorgen.
Hieronder kan je kiezen welke cookies je wilt inschakelen:
Technische en functionele cookies
Deze cookies zijn essentieel om de website goed te laten functioneren, en laten je toe om bijvoorbeeld in te loggen. Je kan deze cookies niet uitschakelen.
Analytische cookies
Deze cookies verzamelen anonieme informatie over het gebruik van onze website. Op die manier kunnen we de website beter afstemmen op de behoeften van de gebruikers.
Marketingcookies
Deze cookies delen je gedrag op onze website met externe partijen, zodat je op externe platformen relevantere advertenties van Standaard Boekhandel te zien krijgt.
Je kan maximaal 250 producten tegelijk aan je winkelmandje toevoegen. Verwijdere enkele producten uit je winkelmandje, of splits je bestelling op in meerdere bestellingen.
This book addresses the task of circuit sizing optimization. A novel framework is introduced, based on time-domain analysis, genetic algorithm optimization, and distributed processing. The time-domain optimization methodology is based on the step response of the amplifier, which simplifies the circuit evaluation and helps the optimization process to converge faster. Complex and accurate device models (e.g. BSIM3v3) are integrated. The time-domain evaluation of the amplifier is used by the genetic algorithm optimization kernel, in the classification of the genetic individuals. Distributed processing is also employed to address the increasing processing time demanded by the complex circuit analysis, and the accurate models of the circuit devices. Platform assessment is carried by several examples, which have been optimized and successfully used, embedded, in larger systems, such as data converters. A dedicated example of an inverter-based self-biased two-stage amplifier has been designed, laid-out, fabricated, and experimentally evaluated. The measured results are a direct demonstration of the effectiveness of the proposed time-domain optimization methodology.