Patent•
Determination of values of physical parameters of one or several components of an electronic circuit or of a microelectro-mechanical system
07 Nov 2008-
TL;DR: In this article, a method for determining, for each of at least p physical parameters of one or several components of an electronic circuit or of a microelectromechanical system, a number n of experiment values of the physical parameter includes determining n vectors of dimension p, each component of each of the vectors corresponding to one of n initial values of one of physical parameters; and iteratively modifying at least some of the n vectors to bring to a maximum, at least locally for each pair of vectors from among pairs of n vectors, the smallest average of the sum of distances between the
Abstract: A method for determining, for each of at least p physical parameters of one or several components of an electronic circuit or of a microelectromechanical system, a number n of experiment values of the physical parameter includes determining n vectors of dimension p, each component of each of the vectors corresponding to one of n initial values of one of physical parameters; and iteratively modifying at least some of the n vectors to bring to a maximum, at least locally, for each pair of vectors from among pairs of n vectors, the smallest average of the sum of distances between the vectors of said pair projected onto sub-spaces of dimension k, where k belongs to a set of integers ranging between 1 and p and at least comprising 1, 2, and p, the components of each of the n vectors corresponding, at the end of the iterations, to experiment values.
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06 Nov 1986TL;DR: A general purpose pattern recognition method and apparatus comprises a hierarchical network of basic recognizers, each basic recognizer being capable of discriminating a particular feature at a lower level and providing outputs for higher levels of abstraction.
Abstract: A general purpose pattern recognition method and apparatus comprises a hierarchical network of basic recognizers, each basic recognizer being capable of discriminating a particular feature at a lower level and providing outputs for higher levels of abstraction. In a learning mode, a series of sample patterns having a feature are presented as input along with several near-miss patterns. The pattern recognition apparatus learns to recognize the feature by keeping track of which basic recognizers detect patterns containing the feature. In a recognition mode, the invention determines if a presented pattern has the feature by polling the basic recognizers. A summation algorithm calculates the likelihood that the presented pattern has a particular feature.
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Abstract: The rapid layout synthesis of microresonators from high-level engineering specifications is demonstrated. Functional parameters such as resonant frequency, quality factor, and displacement amplitude at resonance are satisfied while simultaneously minimizing a user-specified objective function. A synthesis tool implementing the optimization-based formulation can be used to explore micromechanical design issues and objectives, as illustrated with a polysilicon lateral resonator example modeled in three mechanical degrees of freedom. Layouts for four sets of five different resonators from 3 kHz to 300 kHz are generated, with each set globally optimized to minimize either active device area, electrostatic drive voltage, a weighted combination of area and drive voltage, or to maximize displacement amplitude at resonance.
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Patent•
07 Apr 2004
TL;DR: In this article, a method for modeling a pore structure of a porous material is described, which includes generating an initial model of the porous material, including an interconnected network of passages including a first geometric shape and a second geometric shape.
Abstract: A method is disclosed for modeling a pore structure of a porous material. The method includes generating an initial model of the porous material. The initial model includes an interconnected network of passages including a first geometric shape and a second geometric shape. At least one petrophysical property is calculated from the initial model. At least one geometric parameter in at least one passage of the first geometric shape is adjusted. The at least one petrophysical property is recalculated, and the adjusting and recalculating are repeated until a difference between the calculated petrophysical property and a measured petrophysical property reaches a minimum. In some embodiments, the adjusting and recalculating are repeated until an indeterminacy condition is satisfied.
36 citations
TL;DR: In this paper, the authors present the case against two widespread practices in designing engineering experiments, which are (i) to vary one factor at a time (the OFAT approach) and (ii) to generate experimental points by random selection (the Monte Carlo approach).
Abstract: This paper presents the case against two widespread practices in designing engineering experiments, which are (i) to vary one factor at a time (the OFAT approach) and (ii) to generate experimental points by random selection (the Monte Carlo approach). These approaches do not produce good experimental designs, defined as generating maximum information per run (IPR), and should be replaced by designs that do. These latter designs (i) vary many factors at a time and (ii) use a patterned set of experimental points rather than a random set. An example from circuit design is used to illustrate this approach. The limitations of the random approach are well known amongst statisticians but often not among engineers. 1998 John Wiley & Sons, Ltd.
10 citations
07 Dec 2003
TL;DR: In this article, the expected integrated mean squared error (EIMSE) criterion is used to construct alternative optimal experimental designs for RS metamodels with bias, which explicitly takes bias into account.
Abstract: Often in discrete-event simulation, factors being considered are qualitative such as machine type, production method, job release policy, and factory layout type. It is also often of interest to create a response surface (RS) metamodel for visualization of input-output relationships. Several methods have been proposed in the literature for RS metamodeling with qualitative factors but the resulting metamodels may be expected to predict poorly because of sensitivity to misspecification or bias. This paper proposes the use of the expected integrated mean squared error (EIMSE) criterion to construct alternative optimal experimental designs. This approach explicitly takes bias into account. We use a discrete-event simulation example from the literature, coded in ARENA/spl trade/, to illustrate the proposed method and to compare metamodeling accuracy of alternative approaches computationally.
7 citations