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

The Design and Analysis of Experiments

Neuromorphic computing has come to refer to a variety of brain-inspired computers, devices, and models that contrast the pervasive von Neumann computer architecture This biologically inspired approach has created highly connected synthetic neurons and synapses that can be used to model neuroscience theories as well as solve challenging machine learning problems The promise of the technology is to create a brain-like ability to learn and adapt, but the technical challenges are significant, starting with an accurate neuroscience model of how the brain works, to finding materials and engineering breakthroughs to build devices to support these models, to creating a programming framework so the systems can learn, to creating applications with brain-like capabilities In this work, we provide a comprehensive survey of the research and motivations for neuromorphic computing over its history We begin with a 35-year review of the motivations and drivers of neuromorphic computing, then look at the major research areas of the field, which we define as neuro-inspired models, algorithms and learning approaches, hardware and devices, supporting systems, and finally applications We conclude with a broad discussion on the major research topics that need to be addressed in the coming years to see the promise of neuromorphic computing fulfilled The goals of this work are to provide an exhaustive review of the research conducted in neuromorphic computing since the inception of the term, and to motivate further work by illuminating gaps in the field where new research is needed

A Survey of Neuromorphic Computing and Neural Networks in Hardware.

Fabrication of monolithic lattice-mismatched semiconductor heterostructures with limited area regions having upper portions substantially exhausted of threading dislocations, as well as fabrication of semiconductor devices based on such lattice-mismatched heterostructures.

Lattice-Mismatched Semiconductor Structures with Reduced Dislocation Defect Densities and Related Methods for Device Fabrication

Asynchronous Circuit Design

Defect-free germanium has been demonstrated in SiO2 trenches on silicon via Aspect Ratio Trapping, whereby defects arising from lattice mismatch are trapped by laterally confining sidewalls. Results were achieved through a combination of conventional photolithography, reactive ion etching of SiO2, and selective growth of Ge as thin as 450nm. Full trapping of dislocations originating at the Ge∕Si interface has been demonstrated for trenches up to 400nm wide without the additional formation of defects at the sidewalls. This approach shows great promise for the integration of Ge and/or III-V materials, sufficiently large for key device applications, onto silicon substrates.

Defect reduction of selective Ge epitaxy in trenches on Si(001) substrates using aspect ratio trapping

A new laboratory course at San Jose State University, Advanced Thin Film Processes, integrates fabrication of thin films with design of experiment and statistical analysis of data. In the laboratory section of this course, students work through six multi-week modules that increase in the complexity of design of experiment and statistical analysis of data. The six modules have been developed with a standard format that includes learning objectives, background on the specific thin film process, theory of design of experiment principles, instructor notes, dry lab exercises, experimental plan worksheets, and assessment tools. While the modules were developed for a semiconductor processing class, they can easily be implemented in other engineering classes. The modules have been developed with a robust framework that allows the instructor to teach design of experiments and statistical analysis of data along with the specific engineering principles related to their class.

Teaching design of experiments and statistical analysis of data through laboratory experiments

San Jose State University’s new interdisciplinary curriculum in Microelectronics Process Engineering is described. This baccalaureate program emphasizes hands-on thin-film fabrication experience, manufacturing methods such as statistical process control, and fundamentals of materials science and semiconductor device physics. Each course of the core laboratory sequence integrates fabrication knowledge with process engineering and manufacturing methods. The curriculum development process relies on clearly defined and detailed program and course learning objectives. We also briefly discuss our strategy of making process engineering experiences accessible for all engineering students through both Lab Module and Statistics Module series.

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Microelectronics Process Engineering at San Jose State University: A Manufacturing-Oriented Interdisciplinary Degree Program

We report the electrical characteristics of (n)ZnSe/(p þ )GaAs heterostructure solar cells grown by depositing an n-type ZnSe epilayer using photoassisted metal organic vapor phase epitaxy on p þ type GaAs (1 0 0) substrates. A study of the solar cell efficiency as a function of ZnSe epilayer thickness is also presented. Our preliminary results show that an epilayer thickness of 1.5 lm produced the highest efficiency for the cells tested, (4.27% under AM1.5 conditions, no anti-reflective coating). We also demonstrate a method to pattern ZnSe/GaAs structures with an inexpensive methanol/ bromine etch process. 2003 Elsevier Science Ltd. All rights reserved.

Photoassisted MOVPE grown (n)ZnSe/(p+)GaAs heterojunction solar cells

A compact fixed-point digital implementation of a quadratic integrate-and-fire (QIF) neural model was developed. Equations were derived to determine the minimum number of bits the digital QIF model requires to represent all four states of the QIF model and control the switching threshold of the output voltage. In addition, the equations were used to minimize the size of the multiplier used for the nonlinear squaring function, V2. These design equations were used to develop test vectors that could unambiguously show all four states of a digital QIF model. The FPGA implementation of the QIF model was shown to be computationally efficient, requiring only two fixed-point adders and one fixed-point multiplier.

Compact digital implementation of a quadratic integrate-and-fire neuron

Silicon neurons are of importance both to implement hybrid electronic-biological system as well as to develop fundamental understanding of the neurobiological systems they emulate. We have implemented a hardware version of the quadratic integrate and fire neural model. The quadratic integrate and fire neuron differs from the more common integrate and fire neuron in that the model, and thus the hardware, intrinsically generate spikes. Readily available discrete surface mount components are used to make the hardware available to a wider audience and facilitate experimentation.

David W Parent

Papers

Teaching design of experiments and statistical analysis of data through laboratory experiments

Microelectronics Process Engineering at San Jose State University: A Manufacturing-Oriented Interdisciplinary Degree Program

Photoassisted MOVPE grown (n)ZnSe/(p+)GaAs heterojunction solar cells

Compact digital implementation of a quadratic integrate-and-fire neuron

An analog circuit implementation of a quadratic integrate and fire neuron