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Simulation and Verification of Electronic and Biological Systems provides a showcase for the Circuit and Multi-Domain Simulation Workshop held in San Jose, California, USA, on November 5, 2009. The nine chapters are contributed by experts in the field and provide a broad discussion of recent developments on simulation, modeling and verification of integrated circuits and biological systems. Specific topics include large scale parallel circuit simulation, industrial practice of fast SPICE simulation, structure-preserving model order reduction of interconnects, advanced simulation techniques for oscillator networks, dynamic stability of static memories and biological systems as well as verification of analog integrated circuits. Simulation and verification are fundamental enablers for understanding, analyzing and designing an extremely broad range of engineering and biological circuits and systems. The design of nanometer integrated electronic systems and emerging biomedical applications have stimulated the development of novel simulation and verification techniques and methodologies. Simulation and Verification of Electronic and Biological Systems provides a broad discussion of recent advances on simulation, modeling and verification of integrated circuits and biological systems and offers a basis for stimulating new innovations.
Simulation and Verification of Electronic and Biological Systems provides a showcase for the Circuit and Multi-Domain Simulation Workshop held in San Jose, California, USA, on November 5, 2009. The nine chapters are contributed by experts in the field and provide a broad discussion of recent developments on simulation, modeling and verification of integrated circuits and biological systems. Specific topics include large scale parallel circuit simulation, industrial practice of fast SPICE simulation, structure-preserving model order reduction of interconnects, advanced simulation techniques for oscillator networks, dynamic stability of static memories and biological systems as well as verification of analog integrated circuits. Simulation and verification are fundamental enablers for understanding, analyzing and designing an extremely broad range of engineering and biological circuits and systems. The design of nanometer integrated electronic systems and emerging biomedical applications have stimulated the development of novel simulation and verification techniques and methodologies. Simulation and Verification of Electronic and Biological Systems provides a broad discussion of recent advances on simulation, modeling and verification of integrated circuits and biological systems and offers a basis for stimulating new innovations.
This book presents outstanding contributions in an exciting, new and multidisciplinary research area: the application of formal, automated reasoning techniques to analyse complex models in systems biology and systems medicine. Automated reasoning is a field of computer science devoted to the development of algorithms that yield trustworthy answers, providing a basis of sound logical reasoning. For example, in the semiconductor industry formal verification is instrumental to ensuring that chip designs are free of defects (or “bugs”). Over the past 15 years, systems biology and systems medicine have been introduced in an attempt to understand the enormous complexity of life from a computational point of view. This has generated a wealth of new knowledge in the form of computational models, whose staggering complexity makes manual analysis methods infeasible. Sound, trusted, and automated means of analysing the models are thus required in order to be able to trust their conclusions. Above all, this is crucial to engineering safe biomedical devices and to reducing our reliance on wet-lab experiments and clinical trials, which will in turn produce lower economic and societal costs. Some examples of the questions addressed here include: Can we automatically adjust medications for patients with multiple chronic conditions? Can we verify that an artificial pancreas system delivers insulin in a way that ensures Type 1 diabetic patients never suffer from hyperglycaemia or hypoglycaemia? And lastly, can we predict what kind of mutations a cancer cell is likely to undergo? This book brings together leading researchers from a number of highly interdisciplinary areas, including: · Parameter inference from time series · Model selection · Network structure identification · Machine learning · Systems medicine · Hypothesis generation from experimental data · Systems biology, systems medicine, and digital pathology · Verification of biomedical devices “This book presents a comprehensive spectrum of model-focused analysis techniques for biological systems ...an essential resource for tracking the developments of a fast moving field that promises to revolutionize biology and medicine by the automated analysis of models and data.”Prof Luca Cardelli FRS, University of Oxford
This book focuses on an Integrated Design Validation (IDV) system that provides a framework for design validation and takes advantage of current technology in the areas of simulation and formal verification resulting in a practical validation engine with reasonable runtime. After surveying the basic principles of formal verification and simulation, this book describes the IDV approach to integrated circuit functional validation. Table of Contents: Introduction / Formal Methods Background / Simulation Approaches / Integrated Design Validation System / Conclusion and Summary
Electronic systems, including computers and telecommunications, are increasing rapidly in size and complexity. It is no longer practical to build an actual prototype. It is possible now, however, to simulate the design of a prototype without actually building the hardware. This book describes the structure of simulators suitable for use in the design of digital electronic systems. It includes the compiled code and event driven algorithms for digital electronic system simulators, together with timing verification. It also discusses limitations of the structures and problems of designing models. It also covers the subjects of testing and design for testability, and a major chapter is devoted to fault simulation. Finally, the text introduces hardware accelerators and modelers. The book is unique for covering simulation, fault simulation, timing verification, and model design in one place, and should make essential reading for electonic engineers involved in hardware design.
A bionic investigation and modeling of organic evolution is described. The project was undertaken to provide a deeper understanding of the adaptive processes involved in organic evolution. Of particular interest was a comparison of self-organizing processes in evolutionary systems and analogous processes in trainable logical networks. The biological prototype for the model is the feral house mouse (Mus musculus) as it exists in semi-isolated populations in the southwestern United States. Special emphasis is given to a balanced lethal genetic system known to exist in the species. Using Monte Carlo techniques, the model simulates, for each individual, such events as the probability of survival, migration, mating, reproduction, mutation, genetic segregation, and natural selection. Implementation of the model on a digital computer is described. Results of experiments performed with the model show that the model behaves in a manner highly analogous to both the biological prototype and to certain aspects of trainable logical networks. Implications and theoretical investigations of the work for future developments in machine intelligence are discussed. (Author).
Numerical simulation and modelling have been growing in importance and seeing steadily increasing practical application. The proliferation of applications and physical domains for which simulation technologies are now needed, compounded by generally increased complexity, has expanded the scope of numerical simulation and modelling within CAD and spurred new research directions. Numerical Simulation and Modelling of Electronic and Biochemical Systems provides an introduction to the fundamentals of numerical simulation, and to the basics of modelling electronic circuits and biochemical reactions. The emphasis is on capturing a minimal set of important concepts succinctly, but concretely enough that the reader will be left with an adequate foundation for further independent exploration. Starting from mathematical models of basic electronic elements, circuits are modelled as nonlinear differential-algebraic equation (DAE) systems. Two basic techniques - quiescent steady state and transient - for solving these differential equations systems are then developed. It is then shown how biochemical reactions can also be modelled deterministically as DAEs. Following this, frequency domain techniques for finding sinusoidal steady states of linear DAEs are developed, as are direct and adjoint techniques for computing parameter sensitivities and the effects of stationary random noise. For readers interested in a glimpse of topics beyond these basics, an introduction to nonlinear periodic steady state methods (harmonic balance and shooting) and the multitime partial differential equation formulation is provided. Also provided is an overview of model order reduction, an important topic of current research that has roots in numerical simulation algorithms. Finally, sample applications of nonlinear oscillator macromodels - in circuits (PLLs), biochemical reaction-diffusion systems and nanoelectronics - are presented.
Addressing the need for full and accurate functional information during the design process, this guide offers a comprehensive overview of functional verification from the points of view of leading experts at work in the electronic-design industry.
Designing complex integrated circuits relies heavily on mathematical methods and calls for suitable simulation and optimization tools. The current design approach involves simulations and optimizations in different physical domains (device, circuit, thermal, electromagnetic) and in a range of electrical engineering disciplines (logic, timing, power, crosstalk, signal integrity, system functionality). COMSON was a Marie Curie Research Training Network created to meet these new scientific and training challenges by (a) developing new descriptive models that take these mutual dependencies into account, (b) combining these models with existing circuit descriptions in new simulation strategies and (c) developing new optimization techniques that will accommodate new designs. The book presents the main project results in the fields of PDAE modeling and simulation, model order reduction techniques and optimization, based on merging the know-how of three major European semiconductor companies with the combined expertise of university groups specialized in developing suitable mathematical models, numerical schemes and e-learning facilities. In addition, a common Demonstrator Platform for testing mathematical methods and approaches was created to assess whether they are capable of addressing the industry’s problems, and to educate young researchers by providing hands-on experience with state-of-the-art problems.
System-level modeling of MEMS - microelectromechanical systems - comprises integrated approaches to simulate, understand, and optimize the performance of sensors, actuators, and microsystems, taking into account the intricacies of the interplay between mechanical and electrical properties, circuitry, packaging, and design considerations. Thereby, system-level modeling overcomes the limitations inherent to methods that focus only on one of these aspects and do not incorporate their mutual dependencies. The book addresses the two most important approaches of system-level modeling, namely physics-based modeling with lumped elements and mathematical modeling employing model order reduction methods, with an emphasis on combining single device models to entire systems. At a clearly understandable and sufficiently detailed level the readers are made familiar with the physical and mathematical underpinnings of MEMS modeling. This enables them to choose the adequate methods for the respective application needs. This work is an invaluable resource for all materials scientists, electrical engineers, scientists working in the semiconductor and/or sensor industry, physicists, and physical chemists.