Patrick DeWilde – författare

"Computer Systems and Software Engineering" is a compilation of 16 state-of-the-art lectures and keynote speeches given at the COMP-EURO '92 conference. The contributions are from researchers, each of whom gives insight into subjects ranging from hardware design through parallelism to computer applications. The book covers the following subjects: hardware design - memory technology, logic design, algorithms and architecture; parallel processing - programming, cellular neural networks and load balancing; and software engineering - machine learning, logic programming and program correctness. There is also information on visualization, the graphical computer interface.

Complex function theory and linear algebra provide much of the basic mathematics needed by engineers engaged in numerical computations, signal processing or control. The transfer function of a linear time invariant system is a function of the complex vari­ able s or z and it is analytic in a large part of the complex plane. Many important prop­ erties of the system for which it is a transfer function are related to its analytic prop­ erties. On the other hand, engineers often encounter small and large matrices which describe (linear) maps between physically important quantities. In both cases similar mathematical and computational problems occur: operators, be they transfer functions or matrices, have to be simplified, approximated, decomposed and realized. Each field has developed theory and techniques to solve the main common problems encountered. Yet, there is a large, mysterious gap between complex function theory and numerical linear algebra. For example, complex function theory has solved the problem to find analytic functions of minimal complexity and minimal supremum norm that approxi­ e. g. , as optimal mate given values at strategic points in the complex plane. They serve approximants for a desired behavior of a system to be designed. No similar approxi­ mation theory for matrices existed until recently, except for the case where the matrix is (very) close to singular.

A modern microelectronic circuit can be compared to a large construction, a large city, on a very small area. A memory chip, a DRAM, may have up to 64 million bit locations on a surface of a few square centimeters. Each new generation of integrated circuit- generations are measured by factors of four in overall complexity -requires a substantial increase in density from the current technology, added precision, a decrease of the size of geometric features, and an increase in the total usable surface. The microelectronic industry has set the trend. Ultra large funds have been invested in the construction of new plants to produce the ultra large-scale circuits with utmost precision under the most severe conditions. The decrease in feature size to submicrons -0.7 micron is quickly becoming availabl- does not only bring technological problems. New design problems arise as well. The elements from which microelectronic circuits are build, transistors and interconnects, have different shape and behave differently than before. Phenomena that could be neglected in a four micron technology, such as the non-uniformity of the doping profile in a transistor, or the mutual capacitance between two wires, now play an important role in circuit design. This situation does not make the life of the electronic designer easier: he has to take many more parasitic effects into account, up to the point that his ideal design will not function as originally planned.

Matrix theory is the lingua franca of everyone who deals with dynamically evolving systems, and familiarity with efficient matrix computations is an essential part of the modern curriculum in dynamical systems and associated computation. This is a master's-level textbook on dynamical systems and computational matrix algebra. It is based on the remarkable identity of these two disciplines in the context of linear, time-variant, discrete-time systems and their algebraic equivalent, quasi-separable systems. The authors' approach provides a single, transparent framework that yields simple derivations of basic notions, as well as new and fundamental results such as constrained model reduction, matrix interpolation theory and scattering theory. This book outlines all the fundamental concepts that allow readers to develop the resulting recursive computational schemes needed to solve practical problems. An ideal treatment for graduate students and academics in electrical and computer engineering, computer science and applied mathematics.

Complex function theory and linear algebra provide much of the basic mathematics needed by engineers engaged in numerical computations, signal processing or control. The transfer function of a linear time invariant system is a function of the complex vari­ able s or z and it is analytic in a large part of the complex plane. Many important prop­ erties of the system for which it is a transfer function are related to its analytic prop­ erties. On the other hand, engineers often encounter small and large matrices which describe (linear) maps between physically important quantities. In both cases similar mathematical and computational problems occur: operators, be they transfer functions or matrices, have to be simplified, approximated, decomposed and realized. Each field has developed theory and techniques to solve the main common problems encountered. Yet, there is a large, mysterious gap between complex function theory and numerical linear algebra. For example, complex function theory has solved the problem to find analytic functions of minimal complexity and minimal supremum norm that approxi­ e. g. , as optimal mate given values at strategic points in the complex plane. They serve approximants for a desired behavior of a system to be designed. No similar approxi­ mation theory for matrices existed until recently, except for the case where the matrix is (very) close to singular.

A modern microelectronic circuit can be compared to a large construction, a large city, on a very small area. A memory chip, a DRAM, may have up to 64 million bit locations on a surface of a few square centimeters. Each new generation of integrated circuit- generations are measured by factors of four in overall complexity -requires a substantial increase in density from the current technology, added precision, a decrease of the size of geometric features, and an increase in the total usable surface. The microelectronic industry has set the trend. Ultra large funds have been invested in the construction of new plants to produce the ultra large-scale circuits with utmost precision under the most severe conditions. The decrease in feature size to submicrons -0.7 micron is quickly becoming availabl- does not only bring technological problems. New design problems arise as well. The elements from which microelectronic circuits are build, transistors and interconnects, have different shape and behave differently than before. Phenomena that could be neglected in a four micron technology, such as the non-uniformity of the doping profile in a transistor, or the mutual capacitance between two wires, now play an important role in circuit design. This situation does not make the life of the electronic designer easier: he has to take many more parasitic effects into account, up to the point that his ideal design will not function as originally planned.

A modern microelectronic circuit can be compared to a large construction, a large city, on a very small area. A memory chip, a DRAM, may have up to 64 million bit locations on a surface of a few square centimeters. Each new generation of integrated circuit- generations are measured by factors of four in overall complexity -requires a substantial increase in density from the current technology, added precision, a decrease of the size of geometric features, and an increase in the total usable surface. The microelectronic industry has set the trend. Ultra large funds have been invested in the construction of new plants to produce the ultra large-scale circuits with utmost precision under the most severe conditions. The decrease in feature size to submicrons -0.7 micron is quickly becoming availabl- does not only bring technological problems. New design problems arise as well. The elements from which microelectronic circuits are build, transistors and interconnects, have different shape and behave differently than before. Phenomena that could be neglected in a four micron technology, such as the non-uniformity of the doping profile in a transistor, or the mutual capacitance between two wires, now play an important role in circuit design. This situation does not make the life of the electronic designer easier: he has to take many more parasitic effects into account, up to the point that his ideal design will not function as originally planned.

Computer Systems and Software Engineering is a compilation of sixteen state-of-the-art lectures and keynote speeches given at the COMPEURO '92 conference. The contributions are from leading researchers, each of whom gives a new insight into subjects ranging from hardware design through parallelism to computer applications. The pragmatic flavour of the contributions makes the book a valuable asset for both researchers and designers alike. The book covers the following subjects: Hardware Design: memory technology, logic design, algorithms and architecture; Parallel Processing: programming, cellular neural networks and load balancing; Software Engineering: machine learning, logic programming and program correctness; Visualization: the graphical computer interface.

Computer Systems and Software Engineering is a compilation of sixteen state-of-the-art lectures and keynote speeches given at the COMPEURO ''92 conference. The contributions are from leading researchers, each of whom gives a new insight into subjects ranging from hardware design through parallelism to computer applications. The pragmatic flavour of the contributions makes the book a valuable asset for both researchers and designers alike. The book covers the following subjects: Hardware Design: memory technology, logic design, algorithms and architecture; Parallel Processing: programming, cellular neural networks and load balancing; Software Engineering: machine learning, logic programming and program correctness; Visualization: the graphical computer interface.