Georges Gielen

Bio: Georges Gielen is an academic researcher from Katholieke Universiteit Leuven. The author has contributed to research in topics: CMOS & Mixed-signal integrated circuit. The author has an hindex of 56, co-authored 753 publications receiving 13987 citations. Previous affiliations of Georges Gielen include Catholic University of Leuven & National Fund for Scientific Research.

Computer-aided design of analog and mixed-signal integrated circuits

Abstract: This survey presents an overview of recent advances in the state of the art for computer-aided design (CAD) tools for analog and mixed-signal integrated circuits (ICs). Analog blocks typically constitute only a small fraction of the components on mixed-signal ICs and emerging systems-on-a-chip (SoC) designs. But due to the increasing levels of integration available in silicon technology and the growing requirement for digital systems to communicate with the continuous-valued external world, there is a growing need for CAD tools that increase the design productivity and improve the quality of analog integrated circuits. This paper describes the motivation and evolution of these tools and outlines progress on the various design problems involved: simulation and modeling, symbolic analysis, synthesis and optimization, layout generation, yield analysis and design centering, and test. This paper summarizes the problems for which viable solutions are emerging and those which are still unsolved.

A Gaussian Process Surrogate Model Assisted Evolutionary Algorithm for Medium Scale Expensive Optimization Problems

Abstract: Surrogate model assisted evolutionary algorithms (SAEAs) have recently attracted much attention due to the growing need for computationally expensive optimization in many real-world applications. Most current SAEAs, however, focus on small-scale problems. SAEAs for medium-scale problems (i.e., 20-50 decision variables) have not yet been well studied. In this paper, a Gaussian process surrogate model assisted evolutionary algorithm for medium-scale computationally expensive optimization problems (GPEME) is proposed and investigated. Its major components are a surrogate model-aware search mechanism for expensive optimization problems when a high-quality surrogate model is difficult to build and dimension reduction techniques for tackling the “curse of dimensionality.” A new framework is developed and used in GPEME, which carefully coordinates the surrogate modeling and the evolutionary search, so that the search can focus on a small promising area and is supported by the constructed surrogate model. Sammon mapping is introduced to transform the decision variables from tens of dimensions to a few dimensions, in order to take advantage of Gaussian process surrogate modeling in a low-dimensional space. Empirical studies on benchmark problems with 20, 30, and 50 variables and a real-world power amplifier design automation problem with 17 variables show the high efficiency and effectiveness of GPEME. Compared to three state-of-the-art SAEAs, better or similar solutions can be obtained with 12% to 50% exact function evaluations.

A 14-bit intrinsic accuracy Q/sup 2/ random walk CMOS DAC

Abstract: In this paper, a 14-bit, 150-MSamples/s current steering digital-to-analog converter (DAC) is presented. It uses the novel Q/sup 2/ random walk switching scheme to obtain full 14-bit accuracy without trimming or tuning. The measured integral and differential nonlinearity performances are 0.3 and 0.2 LSB, respectively; the spurious-free dynamic range is 84 dB at 500 kHz and 61 dB at 5 MHz. Running from a single 2.7-V power supply, it has a power consumption of 70 mW for an input signal of 500 kHz and 300 mW for an input signal of 15 MHz. The DAC has been integrated in a standard digital single-poly, triple-metal 0.5-/spl mu/m CMOS process. The die area is 13.1 mm/sup 2/.

ISAAC: a symbolic simulator for analog integrated circuits

Abstract: The symbolic simulator ISAAC (interactive symbolic analysis of analog circuits) is presented. The program derives all AC characteristics for any analog integrated circuit (time-continuous and switched-capacitor, CMOS, JFET, and bipolar) as symbolic expressions in the circuit parameters. This yields analytic formulas for transfer functions, CMRR (common-mode rejection ratio), PSRR (power-supply rejection ratio), impedances, noise, etc. Two novel features are included in the program. First, the expressions can be simplified with a heuristic criterion based on the magnitudes of the elements. This yields interpretable formulas showing only the dominant terms. Second, the explicit representation of mismatch terms allows the accurate calculation of second-order effects, such as the PSRR. ISAAC provides analog designers with more insight into the circuit behavior than do numerical simulators and is a useful tool for instruction or designer assistance. Moreover, it generates complete analytic AC circuit models, which are used for automatic sizing in a nonfixed topology analog module generator. The program's capabilities are illustrated with several examples. The efficiency is established by a dedicated sparse-matrix algorithm. >

Symbolic Analysis for Automated Design of Analog Integrated Circuits

Abstract: 1. Introduction to Analog Design Automation.- 1.1. Introduction.- 1.2. Definitions in analog design automation.- 1.3. Characteristics of analog design.- 1.4. Needs for analog circuits and analog design automation.- 1.5. Different analog design approaches and analog silicon compilation.- 1.6. Analog system-level synthesis.- 1.7. Outline of the book.- 2. The Automated Design of Analog Functional Modules.- 2.1. Introduction.- 2.2. Classification of analog module design programs.- 2.3. An automated design methodology for analog modules.- 2.4. The methodology applied to a simple example.- 2.5. Discussion of and comparison with other analog design systems.- 2.6. Conclusions.- 3. Symbolic Simulation of Analog Integrated Circuits.- 3.1. Introduction.- 3.2. Definition and scope of symbolic simulation.- 3.3. Applications of symbolic analysis in analog design.- 3.4. General description of the ISAAC program.- 3.5. Conclusions.- 4. Algorithmic Aspects of Linear Symbolic Simulation.- 4.1. Introduction.- 4.2. Overview of symbolic analysis techniques.- 4.3. The set-up of the linear circuit equations.- 4.4. The symbolic solution of sets of linear equations.- 4.5. Symbolic expression approximation.- 4.6. Performance of the ISAAC program.- 4.7. Conclusions.- 5. Symbolic Distortion Analysis.- 5.1. Introduction.- 5.2. Symbolic noise analysis.- 5.3. Symbolic analysis of harmonic distortion in weakly nonlinear analog circuits.- 5.4. Symbolic sensitivity analysis and zero/pole extraction.- 5.5. Techniques for the hierarchical symbolic analysis of large circuits.- 5.6. Conclusions.- 6. Analog Design Optimization Based on Analytic Models.- 6.1. Introduction.- 6.2. Circuit sizing based on an optimization of analytic models.- 6.3. The analog design formulation in OPTIMAN.- 6.4. Practical design examples.- 6.5. Automated layout generation of analog integrated circuits.- 6.6. Conclusions.- Appendix A. Characterization of a CMOS Two-Stage OPAMP.- References.

The Design and Analysis of Experiments

Abstract: THE DESIGN AND ANALYSIS OF EXPERIMENTS. By Oscar Kempthorne. New York, John Wiley and Sons, Inc., 1952. 631 pp. $8.50. This book by a teacher of statistics (as well as a consultant for \"experimenters\") is a comprehensive study of the philosophical background for the statistical design of experiment. It is necessary to have some facility with algebraic notation and manipulation to be able to use the volume intelligently. The problems are presented from the theoretical point of view, without such practical examples as would be helpful for those not acquainted with mathematics. The mathematical justification for the techniques is given. As a somewhat advanced treatment of the design and analysis of experiments, this volume will be interesting and helpful for many who approach statistics theoretically as well as practically. With emphasis on the \"why,\" and with description given broadly, the author relates the subject matter to the general theory of statistics and to the general problem of experimental inference. MARGARET J. ROBERTSON

Science and technology roadmap for graphene, related two-dimensional crystals, and hybrid systems

Abstract: We present the science and technology roadmap for graphene, related two-dimensional crystals, and hybrid systems, targeting an evolution in technology, that might lead to impacts and benefits reaching into most areas of society. This roadmap was developed within the framework of the European Graphene Flagship and outlines the main targets and research areas as best understood at the start of this ambitious project. We provide an overview of the key aspects of graphene and related materials (GRMs), ranging from fundamental research challenges to a variety of applications in a large number of sectors, highlighting the steps necessary to take GRMs from a state of raw potential to a point where they might revolutionize multiple industries. We also define an extensive list of acronyms in an effort to standardize the nomenclature in this emerging field.

Wireless Networks With RF Energy Harvesting: A Contemporary Survey

Abstract: Radio frequency (RF) energy transfer and harvesting techniques have recently become alternative methods to power the next-generation wireless networks As this emerging technology enables proactive energy replenishment of wireless devices, it is advantageous in supporting applications with quality-of-service requirements In this paper, we present a comprehensive literature review on the research progresses in wireless networks with RF energy harvesting capability, which is referred to as RF energy harvesting networks (RF-EHNs) First, we present an overview of the RF-EHNs including system architecture, RF energy harvesting techniques, and existing applications Then, we present the background in circuit design as well as the state-of-the-art circuitry implementations and review the communication protocols specially designed for RF-EHNs We also explore various key design issues in the development of RF-EHNs according to the network types, ie, single-hop networks, multiantenna networks, relay networks, and cognitive radio networks Finally, we envision some open research directions

Differential Equations and Dynamical Systems

Abstract: Series Preface * Preface to the Third Edition * 1 Linear Systems * 2 Nonlinear Systems: Local Theory * 3 Nonlinear Systems: Global Theory * 4 Nonlinear Systems: Bifurcation Theory * References * Index

Multiobjective evolutionary algorithms: A survey of the state of the art

Abstract: A multiobjective optimization problem involves several conflicting objectives and has a set of Pareto optimal solutions. By evolving a population of solutions, multiobjective evolutionary algorithms (MOEAs) are able to approximate the Pareto optimal set in a single run. MOEAs have attracted a lot of research effort during the last 20 years, and they are still one of the hottest research areas in the field of evolutionary computation. This paper surveys the development of MOEAs primarily during the last eight years. It covers algorithmic frameworks such as decomposition-based MOEAs (MOEA/Ds), memetic MOEAs, coevolutionary MOEAs, selection and offspring reproduction operators, MOEAs with specific search methods, MOEAs for multimodal problems, constraint handling and MOEAs, computationally expensive multiobjective optimization problems (MOPs), dynamic MOPs, noisy MOPs, combinatorial and discrete MOPs, benchmark problems, performance indicators, and applications. In addition, some future research issues are also presented.