Fixed-Point Filters – Modelling and Verification Using Python

NEW: All files related to this workshop have been zipped and can be downloaded by clicking on the link in the left column "Click Here to Download Slides (PDF)"

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 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. For a more detailed review of binary fixed-point operations and notations that will be used in this workshop, please attend Dan's Theatre Talk "Fixed-Point Made Easy: A Guide for Newcomers and Seasoned Engineers" that will be scheduled before this. 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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Quick Start on Control Loops with Python

Control loops are ubiquitous in various applications where we wish to maintain or stabilize process variables to a desired set point or value. The speaker, Dan Boschen, brings a wealth of experience in the mixed signal (digital or analog) practical control loop design of microwave synthesizers, modems and radio transceivers, and, most recently, atomic clocks.

In this live workshop, Dan will first provide an overview of control loop theory sufficient for the implementation of a Phase-Lock-Loop (PLL). Topics covered will include:

• Transfer Functions
• Loop Order and Tracking
• Stability
• Bode and Nyquist Plots
• Noise Transfer Functions

PLL implementations in both the analog and all-digital domain will be detailed for practical implementation. The modeling and simulation of control loops will be demonstrated with use of the free Python programming language.

This is a great opportunity for anyone wishing to get a quick jump start on practical control loop implementations in both the digital and analog domains, and to see what Python can offer for use in the simulation and modeling of control loops. 

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Demystifying the Hilbert Transform

Workshop Description

In this workshop, Dan will introduce the Hilbert Transform and the Analytic Signal, and the various uses for them. Dan will review the fundamental points in understanding the Hilbert Transform intuitively and then he will show practical implementations and applications both in the analog and digital signal processing domains. Key limitations and gotchas will be presented that every designer should be aware of. Dan will demonstrate creative implementations using Python, and provide similar scripts compatible with MATLAB. Attendees will gain a more intuitive insight of key signal processing concepts using complex signals that are applicable to a wide range of applications.

Workshop Instructions

Thank you for your interest in the Demystifying the Hilbert Transform workshop! Below are the installation instructions for Python in case you want to follow along hands-on with the examples given or run the examples later.

Option 1: Easy path to Python: Install the Anaconda Individual Edition which will have all the tools we will be using: https://www.anaconda.com/products/individual

Option 2: Alternative manual path to Python: As a minimum install we will be using Python 3, Numpy, Matplotlib, and Scipy:

     Install python: https://www.python.org/downloads/

     From command window type: 

         pip install ipython 

         pip install numpy

         pip install matplotlib

         pip install scipy

         (if you encounter any difficulty with installing the packages, see this page: https://packaging.python.org/tutorials/installing-packages/)

Note: We will not be debugging any installation issues in the Workshop, and a Python installation is not necessary to follow along with the workshop presentation. Having a Python installation running with the above libraries is convenient if you want to follow along hands-on, as Dan will be demonstrating the material using Python. A Jupyter Notebook of the material presented will also be distributed here after the workshop for future reference, along with similar scripts that work in Matlab or Octave. If you would like further basics on running the Notebook, please see this link:

https://www.datacamp.com/community/tutorials/tutorial-jupyter-notebook

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Fast Track to Designing FIR Filters with Python

Thank you for your interest in the Fast Track to Designing FIR Filters with Python workshop! Below are the installation instructions as well as a Jupyter Notebook with the material that will be presented in the workshop.

Option 1: Easy path to Python: Install the Anaconda Individual Edition which will have all the tools we will be using: https://www.anaconda.com/products/individual

Option 2: Alternative manual path to Python: As a minimum install we will be using Python 3, Numpy, Matplotlib, and Scipy:

     Install python: https://www.python.org/downloads/

     From command window type: 

         pip install ipython 

         pip install numpy

         pip install matplotlib

         pip install scipy

         (if you encounter any difficulty with installing the packages, see this page: https://packaging.python.org/tutorials/installing-packages/)

Being able to run Jupyter Notebooks is not necessary for the workshop but convenient as I am sharing the details of the workshop in the attached Jupyter Notebook for future reference. If you would like further basics on running the Notebook, please see this link:

https://www.datacamp.com/community/tutorials/tutorial-jupyter-notebook

Notebook: Fast Track FIR Filter Workshop.ipynb

Finite Impulse Response (FIR) filters are the more popular of the two main types of digital filter implementations used in DSP applications. In this workshop, we will go through best practice approaches for optimized FIR filter design and implementation using the free and open-source Python programming language. This will include the common techniques for going from filter requirements to practical implementation and demonstrate both creating FIR filter designs as well as evaluating filter frequency responses using the Python language and its signal processing library.

This workshop will include:

• Complete setup to get Python up and running for signal processing applications.
• Summary of the high-level approaches to FIR filter design – which are best and why?
• Fast track to using the signal processing library in Python for creating FIR designs.
• The complete design flow for FIR filters from specification through verification.
• Using Python for filter evaluation, including plotting magnitude and phase responses.

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