Abstract: The invention relates to a computer-supported, automated method for the verification of analog circuits, and to a storage medium on which a computer software program is stored for performing such method, including transforming of constants or variables characterizing a first equation system for describing the properties of a circuit; transforming of constants or variables characterizing a second equation system for describing the properties of a circuit; and performing a circuit equivalence test by using the transformed quantities obtained from transforming.

Abstract: A method for adaptively generating a series of random numbers of a 1/f noise is based on the use of normally distributed random numbers. The method enables a need-oriented generation of random numbers of the 1/f noise, whereby additional random numbers of the 1/f noise are also possible during a simulation calculation.

Abstract: A computer-aided method for parallel calculation of the operating point of electrical circuits has the circuit partitioned into a number of partitions in a first step, in which the charging method is used for the parallel calculation of the individual partitions.

Abstract: The invention relates to a computer-supported, automated method for the verification of analog circuits (1), and to a storage medium on which a computer software program is stored for performing such method, said method comprising the steps of: transforming of constants or variables (A1, x1), respectively, characterizing a first equation system for describing the properties of a circuit; transforming of constants or variables (A2, x2), respectively, characterizing a second equation system for describing the properties of a circuit; performing a circuit equivalence test by using the transformed quantities (z) obtained from transforming.

Abstract: A computer programmed to process a method for generating a sequence of random numbers of a 1/f noise has the following steps: 1). Determining a constant step &dgr; or instants of consideration t0 to tn; 2). Determining a desired spectral value &bgr;; 3). Determining the number n of the random numbers, to be generated, of a 1/f noise; 4). Determining an intensity constant const; 5). forming a covariance matrix C of dimension (n×n); and 6). Forming the Cholesky decomposition L of the covariance matrix C, with the following steps being carried out for each sequence, to be generated, of random numbers of a 1/f noise: 1). Forming a vector x of length n from random numbers normally distributed in [0,1], and 2). Generating a vector y of length n of the desired 1/f-distributed random numbers by multiplying the Cholesky-decomposition L by the vector x.

Abstract: A method for adaptively generating a series of random numbers of a 1/f noise is based on the use of normally distributed random numbers. The method enables a need-oriented generation of random numbers of the 1/f noise, whereby additional random numbers of the 1/f noise are also possible during a simulation calculation.

Abstract: A method for generating a sequence of random numbers approximated to sequences of numbers of a 1/f noise is based on utilizing (0,1)-normally-distributed random numbers to make possible the generation of an arbitrary-length sequence of random numbers representing a good approximation to random numbers of a 1/f noise while limiting the computation time for determining such sequences of random numbers.

Abstract: A technical system that is subject to a malfunction is described with an implicit stochastic differential equation system. An approximative solution of the system is determined in that a discrete approximation process is realized. The discrete approximation process is realized according to the following rule: −(C+h&agr;2G)·{tilde over (X)}&pgr;n+1={−(1−&ggr;)C+h(1+&ggr;&agr;1−&agr;2)G}·{tilde over (X)}&pgr;n+ +{−&ggr;C+h(&ggr;−&agr;1&ggr;)G}·{tilde over (X)}&pgr;n+1 +h&agr;2s(&pgr;n+1)+h(1+&ggr;&agr;1−&agr;2)s(&pgr;n)+ +h(&ggr;−&agr;1&ggr;)s(&pgr;n−1)+ +B(&pgr;n)·&Dgr;Wn+&ggr;B(&pgr;n)·&Dgr;Wn−1 The disturbance {tilde over (X)}&pgr;n+1 is determined by iterative solution of the approximation process.