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Analog Design Centering and Sizing by Helmut E. Graeb PDF

By Helmut E. Graeb

ISBN-10: 1402060033

ISBN-13: 9781402060038

ISBN-10: 1402060041

ISBN-13: 9781402060045

What you’ll locate here's a attention-grabbing compendium of primary challenge formulations of analog layout centering and sizing. This crucial paintings offers a differentiated wisdom concerning the initiatives of analog layout centering and sizing. specifically, worst-case situations are formulated and analyzed. This paintings is true on the crossing element among technique and layout expertise, and is either reference paintings and textbook for realizing CAD tools in analog sizing.

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Sample text

Statistical-yield optimization is based on a statistical estimation of the yield. The underlying statistical yield analysis is done by means of a Monte-Carlo analysis. Please note that the term statistical-yield optimization refers to the statistical estimation of the yield, but not to the optimization method. Geometric-yield optimization replaces the statistical estimation of yield by a yield approximation that is based on geometric considerations. The manufacturing variations are described by a probability density function of statistical parameters.

In this work, deterministic solution methods for yield optimization/design centering that use gradients will be formulated in Chapter 7. It is important to note that numerical optimization is not only required for yield optimization/design centering and performance optimization, but for tasks that are named analysis in Figure 13. Worst-case analysis as well as geometric yield analysis will turn out to be optimization problems as well. 3. Optimization methods applied to sizing generally have to frequently evaluate the optimization objective.

The objective and the solution approach either can be statistical or deterministic. 7. This allows a unified view on the yield optimization/design centering tasks. Another way to characterize optimization tasks is according to the usage of gradients in the solution approach. While statistical optimization methods often work without gradients, deterministic optimization methods often are based on gradients and second-order derivatives. In this work, deterministic solution methods for yield optimization/design centering that use gradients will be formulated in Chapter 7.

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Analog Design Centering and Sizing by Helmut E. Graeb


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