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Dan Boschen

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.

Fixed-Point Filters – Modelling and Verification Using Python

Status: Coming up in April 2023!

Digital filters are commonly used in the processing of signals, whether they be wireless waveforms, captured sounds, and biomedical signals such as ECG; typically for the purpose of passing certain frequencies and suppressing others. Fixed-point implementation is attractive for lowest power lowest cost solutions when it is critical to make the most out of limited computing resources, however there can be significant performance challenges when implementing filters in fixed-point binary arithmetic. When a fixed-point implementation is required, a typical design process is to start with a floating-point design that has been validated to meet all performance requirements, and then simulate a fixed-point implementation of that design while modifying the precision used to ensure the requirements are met.

In this workshop, Dan takes you through the practical process of simulating a fixed-point digital filter using open-source Python libraries. This is of interest to participants wanting to see a motivating example for learning Python as well as those with experience using Python. Also included: a quick recap of binary Q- notation, basic filter structures, and filter performance concerns. A significant background in Digital Signal Processing (DSP) or digital filter design is not required. Having taken an undergraduate Signals and Systems course is sufficient. After attending this talk, the participants will be equipped to confidently convert a given filter implementation to fixed-point prior to detailed implementation. If you have a floating-point filter design and need to implement it in fixed-point, this workshop is for you!

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