IEEE Boston Section

COURSE DESCRIPTION First Video Release, Wednesday, September 7, 2022.   Additional videos released weekly in advance of that week’s live session! Live Workshops:  6:00PM – 7:30PM EDT, Tuesdays, September 13, 20, 27, October 4 Attendees will have access to the recorded session and exercises for two months (until December 4) after the live session ends!     IEEE Member Fee:  $190.00 Non-Member Fee:  $210.00 Decision to run/cancel course:  Friday, September 2, 2022 Speaker:  Dan Boschen This is a hands-on course combining pre-recorded lectures with live Q&A and workshop sessions in the popular and powerful open-source Python programming language. New Format with Pre-Recorded Videos:  The course format has been updated to release pre-recorded video lectures that students can watch on their own schedule, and an unlimited number of times, prior to live Q&A workshop sessions on Zoom with the instructor. The videos will also be available to the students for viewing for up to two months after the conclusion of the course. Overview: Dan provides simple, straight-forward navigation through the multiple configurations and options, providing a best-practices approach for quickly getting up to speed using Python for modelling and analysis for applications in signal processing and digital design verification. Students will be using the Anaconda distribution, which combines Python with the most popular data science applications, and Jupyter Notebooks for a rich, interactive experience. The course begins with basic Python data structures and constructs, including key “Pythonic” concepts, followed by an overview and use of popular packages for scientific computing enabling rapid prototyping for system design. During the course students will create example designs including a sigma delta converter and direct digital synthesizer both in floating point and fixed point. This will include considerations for cycle and bit accurate models useful for digital design verification (FPGA/ASIC), while bringing forward the signal processing tools for frequency and time domain analysis. Jupyter Notebooks: This course makes extensive use of Jupyter Notebooks which combines running Python code with interactive plots and graphics for a rich user experience. Jupyter Notebooks is an open-source web-based application (that can be run locally) that allows users to create and share visually appealing documents containing code, graphics, visualizations and interactive plots. Students will be able to interact with the notebook contents and use “take-it-with-you” results for future applications in signal processing. Target Audience: This course is targeted toward users with little to no prior experience in Python, however familiarity with other modern programming languages and an exposure to object-oriented constructs is very helpful. Students should be comfortable with basic signal processing concepts in the frequency and time domain. Familiarity with Matlab or Octave is not required, but the equivalent operations in Python using the NumPy package will be provided for those students that do currently use Matlab and/or Octave for signal processing applications. Benefits of Attending / Goals of Course: Attendees will gain an overall appreciation of using Python and quickly get up to speed in best practice use of Python and related tools specific to modeling and simulation for signal processing analysis and design. All set-up information for the installation of all tools will be provided before the start of class. Topics / Schedule: Pre-recorded lectures (3 hours each) will be distributed Friday prior to all Workshop dates. Workshop/ Q&A Sessions are 7pm-8pm on the dates listed below: Tuesday, September 13 Topic 1: Intro to Jupyter Notebooks, the Spyder IDE and the course design examples. Core Python constructs. Tuesday, September 20 Topic 2: Core Python constructs; iterators, functions, reading writing data files. Tuesday, September 27 Topic 3: Signal processing simulation with popular packages including NumPy, SciPy, and Matplotlib. Tuesday, October 4

Topic 4: Bit/cycle accurate modelling and analysis using the design examples and simulation packages

Speaker’s Bio:

Dan Boschen has a MS in Communications and Signal Processing from Northeastern University, with over 25 years of experience in system and hardware design for radio transceivers and modems. He has held various positions at Signal Technologies, MITRE, Airvana and Hittite Microwave designing and developing transceiver hardware from baseband to antenna for wireless communications systems and has taught courses on DSP to international audiences for over 15 years. Dan is a contributor to Signal Processing Stack Exchange https://dsp.stackexchange.com/, and is currently at Microchip (formerly Microsemi and Symmetricom) leading design efforts for advanced frequency and time solutions. For more background information, please view Dan’s Linked-In page.

Computer Society and GBC/ACM

Programming is (should be) fun!

Gerald Jay Sussman, MIT

Register in advance for this webinar at

https://acm-org.zoom.us/webinar/register/6416598165396/WN_rytdvV-vQ2u8I9oICZzXBg

After registering, you will receive a confirmation email containing information about joining the webinar.

Programming is not coding! Programming is a medium for creative expression. Composing a good program can be an esthetic experience similar to writing a story, a piece of music, or poetry,

A good programming experience is an exploration of abstract design. A successful design requires careful choice of the levels of detail for each layer of a programming project. Some of these choices involve classical issues of philosophy, such as the status of referents of expressions, the meaning of quotation, the problems with negation, the power of self-reference, and the use (and danger) of abstraction. Well-composed programs can be effective at expressing emotional content as well. There are the beauties of symmetrical design, and the horrors of ugly kludges.

All programs have bugs, even ones that meet given specs (because the specs are always incomplete or inconsistent). Bugs are inevitable because the creation of buggy approximations is a crucial part of the design process. Thus, it is more effective to make systems that are debuggable than to try to make systems that are correct by construction.

In any case, we must keep the fun in programming and not allow it to become a tedious job.

Bio:  Gerald Jay Sussman is the Panasonic (formerly Matsushita) Professor of Electrical Engineering at the Massachusetts Institute of Technology. He received the S.B. and the Ph.D. degrees in mathematics from the Massachusetts Institute of Technology in 1968 and 1973, respectively. He has been involved in artificial intelligence research at M.I.T. since 1964. His research has centered on understanding the problem-solving strategies used by scientists and engineers, with the goals of automating parts of the process and formalizing it to provide more effective methods of science and engineering education. Sussman has also worked in computer languages, in computer architecture and in VLSI design.

Sussman is a coauthor (with Hal Abelson and Julie Sussman) of the introductory computer science textbook used at M.I.T. for 23 years. The textbook, “Structure and Interpretation of Computer Programs,” has been translated into French, German, Chinese, Polish, Japanese, and Korean. As a result of this and other contributions to computer-science education, Sussman received the ACM’s Karl Karlstrom Outstanding Educator Award in 1990, and the Amar G. Bose award for teaching in 1992.

Sussman’s contributions to Artificial Intelligence include problem solving by debugging almost-right plans, propagation of constraints applied to electrical circuit analysis and synthesis, dependency-based explanation and dependency-based backtracking, and various language structures for expressing problem-solving strategies. Sussman and his former student Guy L. Steele Jr. invented the Scheme programming language in 1975.

Sussman saw that Artificial Intelligence ideas can be applied to computer-aided design. Sussman developed, with his graduate students, sophisticated computer-aided design tools for VLSI. Steele made the first Scheme chips in 1978. These ideas and the AI-based CAD technology to support them were further developed in the Scheme chips of 1979 and 1981. The technique and experience developed was then used to design other special-purpose computers. Sussman was the principal designer of the Digital Orrery, a machine designed to do high-precision integrations for orbital-mechanics experiments. The Orrery was designed and built by a few people in a few months, using AI-based simulation and compilation tools.

Using the Digital Orrery, Sussman worked with Jack Wisdom to discover numerical evidence for chaotic motions in the outer planets. The Digital Orrery is now retired at the Smithsonian Institution in Washington DC. Sussman was also the lead designer of the Supercomputer Toolkit, another multiprocessor computer optimized for evolving systems of ordinary differential equations. The Supercomputer Toolkit was used by Sussman and Wisdom to confirm and extend the discoveries made with the Digital Orrery to include the entire planetary system.

Sussman has pioneered the use of computational descriptions to communicate methodological ideas in teaching subjects in Electrical Circuits and in Signals and Systems. Over the past decades Sussman and Wisdom have developed a subject that uses computational techniques to communicate a deeper understanding of advanced Classical Mechanics. Computational algorithms are used to express the methods used in the analysis of dynamical phenomena. Expressing the methods in a computer language forces them to be unambiguous and computationally effective. Students are expected to read our programs and to extend them and to write new ones. The task of formulating a method as a computer-executable program and debugging that program is a powerful exercise in the learning process. Also, once formalized procedurally, a mathematical idea becomes a tool that can be used directly to compute results. Sussman and Wisdom have produced a textbook, “Structure and Interpretation of Classical Mechanics,” and a monograph, “Functional Differential Geometry,” to capture these ideas. The textbook is now in a second edition.

Sussman is a life fellow of the Institute of Electrical and Electronics Engineers (IEEE). He is a member of the National Academy of Engineering (NAE), a fellow of the American Association for Artificial Intelligence (AAAI), a fellow of the Association for Computing Machinery (ACM), a fellow of the American Academy of Arts and Sciences, and a fellow of the American Association for the Advancement of Science (AAAS).

This joint meeting of the Boston Chapter of the IEEE Computer Society and GBC/ACM will be online only due to the COVID-19 lockdown.

Up-to-date information about this and other talks is available online at https://ewh.ieee.org/r1/boston/computer/.

You can sign up to receive updated status information about this talk and informational emails about future talks at https://mailman.mit.edu/mailman/listinfo/ieee-cs, our self-administered mailing list.

HPEC is the largest computing conference in New England and is the premier conference in the world on the convergence of High Performance and Embedded Computing. We are passionate about performance. Our community is interested in computing hardware, software, systems and applications where performance matters. We welcome experts and people who are new to the field.

The 2021 HPEC technical committee seeks new presentations that clearly describe advances in high performance extreme computing technologies.

The HPEC submission site is open. Submission Deadline is: July 9, 2022!

For more information and deadlines click here:

Microwave Theory & Techniques Society – 6:00PM, Tuesday, September 20

Dual-Band and Broadband RF Power Amplifiers for Concurrent Signal Transmission

Additional information will be posted soon.

Speaker:  Dr. Zurek, Philip

Virtual: Zoom link TBA

COURSE DESCRIPTION

First Video Release, Wednesday, September 7, 2022.   Additional videos released weekly in advance of that week’s live session!

Live Workshops:  6:00PM – 7:30PM EDT, Tuesdays, September 13, 20, 27, October 4

Attendees will have access to the recorded session and exercises for two months (until December 4) after the live session ends!

 

 

IEEE Member Fee:  $190.00

Non-Member Fee:  $210.00

Decision to run/cancel course:  Friday, September 2, 2022

Speaker:  Dan Boschen

This is a hands-on course combining pre-recorded lectures with live Q&A and workshop sessions in the popular and powerful open-source Python programming language.

New Format with Pre-Recorded Videos:  The course format has been updated to release pre-recorded video lectures that students can watch on their own schedule, and an unlimited number of times, prior to live Q&A workshop sessions on Zoom with the instructor. The videos will also be available to the students for viewing for up to two months after the conclusion of the course.

Overview: Dan provides simple, straight-forward navigation through the multiple configurations and options, providing a best-practices approach for quickly getting up to speed using Python for modelling and analysis for applications in signal processing and digital design verification. Students will be using the Anaconda distribution, which combines Python with the most popular data science applications, and Jupyter Notebooks for a rich, interactive experience.

The course begins with basic Python data structures and constructs, including key “Pythonic” concepts, followed by an overview and use of popular packages for scientific computing enabling rapid prototyping for system design.

During the course students will create example designs including a sigma delta converter and direct digital synthesizer both in floating point and fixed point. This will include considerations for cycle and bit accurate models useful for digital design verification (FPGA/ASIC), while bringing forward the signal processing tools for frequency and time domain analysis.

Jupyter Notebooks: This course makes extensive use of Jupyter Notebooks which combines running Python code with interactive plots and graphics for a rich user experience. Jupyter Notebooks is an open-source web-based application (that can be run locally) that allows users to create and share visually appealing documents containing code, graphics, visualizations and interactive plots. Students will be able to interact with the notebook contents and use “take-it-with-you” results for future applications in signal processing.

Target Audience: This course is targeted toward users with little to no prior experience in Python, however familiarity with other modern programming languages and an exposure to object-oriented constructs is very helpful. Students should be comfortable with basic signal processing concepts in the frequency and time domain. Familiarity with Matlab or Octave is not required, but the equivalent operations in Python using the NumPy package will be provided for those students that do currently use Matlab and/or Octave for signal processing applications.

Benefits of Attending / Goals of Course: Attendees will gain an overall appreciation of using Python and quickly get up to speed in best practice use of Python and related tools specific to modeling and simulation for signal processing analysis and design.

All set-up information for the installation of all tools will be provided before the start of class.

Topics / Schedule:

Pre-recorded lectures (3 hours each) will be distributed Friday prior to all Workshop dates. Workshop/ Q&A Sessions are 7pm-8pm on the dates listed below:

Tuesday, September 13

Topic 1: Intro to Jupyter Notebooks, the Spyder IDE and the course design examples. Core Python constructs.

Tuesday, September 20

Topic 2: Core Python constructs; iterators, functions, reading writing data files.

Tuesday, September 27

Topic 3: Signal processing simulation with popular packages including NumPy, SciPy, and Matplotlib.

Tuesday, October 4

Topic 4: Bit/cycle accurate modelling and analysis using the design examples and simulation packages

Speaker’s Bio:

Dan Boschen has a MS in Communications and Signal Processing from Northeastern University, with over 25 years of experience in system and hardware design for radio transceivers and modems. He has held various positions at Signal Technologies, MITRE, Airvana and Hittite Microwave designing and developing transceiver hardware from baseband to antenna for wireless communications systems and has taught courses on DSP to international audiences for over 15 years. Dan is a contributor to Signal Processing Stack Exchange https://dsp.stackexchange.com/, and is currently at Microchip (formerly Microsemi and Symmetricom) leading design efforts for advanced frequency and time solutions.

For more background information, please view Dan’s Linked-In page.