Lecture Series Archive

LED Lighting: Cool and Bright

Benny Smith

Mr. Benny Smith
Visionsmith, Hidden Valley Lake, CA

Thu, 10/18/2018

Abstract - LED lighting is rapidly replacing the incandescent and fluorescent lighting. As LEDs become more efficient and more affordable, they will accelerate the demise of all other forms of lighting. Some interesting questions one can ask are: How much more efficient are they? And, why is that so? Why do they cost so much, relative to an incandescent light? How does an LED work? What kind of power do they require? What is the simplest way to make an LED light? We look at three common applications in automotive, home, and commercial and how practical LED fixtures are designed and what we can expect in the future for LED lighting.

Mr. Benny Smith grew up in Texas and graduated from Texas A&M University with a BSEE degree in 1966. He spent two years in the U.S. Army as a Second Lieutenant (Armor). Benny attained a Teaching Certificate in elementary education in 1971 and taught junior-high math and science for one year. He then pursue graduate work and received his MSEE from Arizona State University in 1976. He worked as a design engineer at Motorola Semiconductor in Phoenix and moved to Sonoma County in 1976 to work at HP’s Santa Rosa Division. Benny retired from Agilent in 2004 and built his first commercial LED light fixture for Visionsmith in 2012.

Basic RF Measurements and Terminology

Wei Lin

Mr. Wei Lin
Senior RF Hardware Design Engineer
National Instruments, Santa Rosa, CA

Thu, 10/04/2018

Abstract - RF and wireless communications technology are standard in everyday device design. Understanding the fundamentals of RF systems and some basic RF Measurements and terminology is critical to your success in designing and testing RF devices. This presentation is going to introduce you some fundamental RF concepts and measurements. We will cover some RF Basic Terminology, Analog and Digital Modulation, some specific topics of common measurement applications like EVM, Phase Noise, Linearity and so on. Further, we will go over different types of measurement instruments and review each one’s advantage and disadvantage in RF application.


Mr. Wei Lin graduated from University of California, Davis in 2012 with a master’s degree of electrical engineering major. After graduation, he joined National Instruments as a RF hardware design engineer. He has been working as a designer, characterization and verification roles on the highperformance vector signal transceiver products from National Instruments.


Learning Large-Scale Sparse Graphical Models: Theory, Algorithm, and Applications

Somayeh Sojoudi

Dr. Somayeh Sojoudi
Assistant Professor
EE & CS Department, UC Berkley

Thu, 09/20/2018

Abstract - Learning models from data has a significant impact on many disciplines, including computer vision, medical imaging, social networks and signal processing. In the network inference problem, one may model the relationships between the network components through an underlying inverse covariance matrix. The sparse inverse covariance estimation problem is commonly solved using an ℓ1-regularized Gaussian maximum likelihood estimator, known as “graphical lasso”. Despite the popularity of graphical lasso, its computational cost becomes prohibitive for large data sets. In this talk, we will develop new notions of sign-consistent matrices and inverse-consistent matrices to obtain key properties of graphical lasso and prove that although the complexity of solving graphical lasso is high, the sparsity pattern of its solution has a simple formula if a sparse graphical model is sought. We will prove — under mild assumptions— that the graphical lasso estimator can be retrieved by soft-thresholding the sample covariance matrix and solving a maximum determinant matrix completion (MDMC) problem, and describe a Newton-CG algorithm to efficiently solve the MDMC problem. We will illustrate our results in different case studies.

Dr. Somayeh Sojoudi is an Assistant Professor in the Departments of Electrical Engineering & Computer Sciences and Mechanical Engineering at UC Berkeley. She is an Associate Editor of the journals of IEEE Transactions on Smart Grid, IEEE Access, and Systems & Control Letters. She is a member of the conference editorial board of the IEEE Control Systems Society. She is a recipient of the 2015 INFORMS Optimization Society Prize for Young Researchers and a recipient of the 2016 INFORMS ENRE Energy Best Publication Award. She was a finalist (as advisor) for the Best Student Paper Award at the 2018 American Control Conference and a finalist (as a co-author) for the best student paper award at the 53rd IEEE Conference on Decision and Control 2014.

Signal Integrity and How It Fits in Your Career

Tim Wang-Lee

Mr. Tim Wang-Lee
Application Engineer
Keysight Technologies, Santa Rosa, CA

Thu, 09/06/2018

Abstract – The large amount of processed digital information and the ever-increasing data rate create a dire need for signal integrity (SI) engineers. By 2021, the monthly global Internet traffic is predicted to reach 278 exabytes, the same amount of data if every individual in the world has a 32 GB IPod touch. In contrast to the narrow band nature of microwave circuit design and analysis, an engineer designing for a high speed digital interface such as USB has to worry about bandwidth from DC all the way up to gigahertz range. Bridging the gap between microwave engineering and signal integrity, this presentation helps kick-start your SI career by demonstrating signal integrity analyses with a practical case study.

Mr. Tim Wang-Lee is an Application Engineer for Signal Integrity and Power Integrity applications in the EEsof EDA Group of Keysight Technologies. Wang Lee is currently a Ph.D candidate concentrating on signal integrity research at the University of Colorado. He received his BSEE degrees from University of Illinois at Urbana Champaign and MSEE from University of Colorado at Boulder. In the past years, he has presented papers in DesignCon focusing on understanding high-speed channels and improving simulation and measurement correlation. Tim is an electromagnetism enthusiast and can recite Maxwell’s equations (in differential form) from memory.

Why Did Silicon Valley Develop in the San Francisco Bay Area Instead of the East Coast?

Don Estreich

Dr. Don Estreich
Engineering Science Department, Sonoma State University, Rohnert Park, CA

Thu, 04/19/2018

Abstract – Silicon Valley is one of the World’s great success stories in the evolution of technology. The roots and origin of Silicon Valley date back to over 100 years ago. It can be argued that it started with the amateur radio activities, within the San Francisco Bay Area, resulting in the development of world-leading vacuum tube technology that would prove crucial to the war effort in World War II. Stanford University, lead by the work of Dr. Fred Terman, were essential in building the environment necessary for the growth of Silicon Valley. Shockley Semiconductor lead to the founding of Fairchild Semiconductor which resulted in the development of the planar process – it enabled the integrated circuit microelectronic revolution. That in turn drove the rise of the personal computer and eventually to the use of the Internet as we know it today. This talk reviews the history of Silicon Valley and explores why it blossomed in the San Francisco Bay Area and not elsewhere. The key elements in the success of Silicon Valley and why it happened in the Bay Area are discussed.

Dr. Don Estreich is currently an Adjunct Professor in the Engineering Science Department at Sonoma State University. He received the BSEE degree from U.C. Berkeley and the Ph.D. from Stanford University in 1980. During the 1970s he worked in Silicon Valley at Hewlett-Packard Laboratories in Palo Alto. He worked for 30 years at Hewlett-Packard’s Technology Center (later Agilent Technologies) on compound semiconductor integrated circuits and test and measurement instrumentation. He has been with Sonoma State University since 2010.