In recent years, reduced-order modeling techniques based on Krylov-subspace iterations, especially the Lanczos algorithm and the Arnoldi process, have become popular tools to tackle the large-scale time-invariant linear dynamical systems that arise in the simulation of electronic circuits. This paper reviews the main ideas of reduced-order modeling techniques based on Krylov subspaces and describes the use of reduced-order modeling in circuit simulation. 1 Introduction Krylov-subspace methods, most notably the Lanczos algorithm [81, 82] and the Arnoldi process [5], have long been recognized as powerful tools for large-scale matrix computations. Matrices that occur in large-scale computations usually have some special structures that allow to compute matrix-vector products with such a matrix (or its transpose) much more efficiently than for a dense, unstructured matrix. The most common structure is sparsity, i.e., only few of the matrix entries are nonzero. Computing a matrix-vector pr...

this paper, we review the Bluetooth technology, a new universal radio interface enabling electronic devices to connect and communicate wirelessly via short-range connections. Motivations for the air interface design and radio requirement decisions are discussed. Frequency hopping, interference resistance, and the concepts of ad hoc connectivity and scatternets are explained in detail. Furthermore, Bluetooth characteristics enabling low-cost single-chip implementations and supporting low power consumption are discussed

In this paper, the design strategy for a circuit synthesis program is described. Unlike other synthesis programs, the program searches in an extremely large set of possible circuits (over 1,000,000 possible circuit configurations), and is not restricted to one device technology. It uses