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John Edwards

John Edwards is a DSP, AI, ML and Embedded Systems Consultant. He has worked as a DSP Engineer since the early 1980s, including wireless and digital communications, control, automotive, IoT and Machine Learning, working for companies such as Loughborough Sound Images, Motorola, Picochip and XMOS Semiconductors. Since 1993 John has been a visiting lecturer at the University of Oxford, presenting the annual Summer Engineering Program for Industry. He is a member of the IET, IEEE and regular contributor at international DSP conferences.

Building A Tensorflow Lite Neural Network Vibration Classifier, With A Little Help From DSP

Available in 17 hours and 36 minutes

This presentation will walk through a Python Notebook that uses a combination of DSP and a Convolutional Neural Network (CNN) to classify multiple vibration modes of a rotating machine.
The key to developing an efficient vibration mode classifier is the use of DSP algorithms to optimize the task.
The DSP functions will pre-process the data to allow a simpler Neural Network to be used for the classification.
The CNN will use a Tensorflow model that is trained on the supplied data, it will then use the model to classify new data.
We will also include the code to generate and test both the Tensorflow and Tensorflow Lite models.
Once generated, we will test the Tensorflow Lite model to ensure it classifies the data as well as the floating point model.

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Live Q&A - Building A Tensorflow Lite Neural Network Vibration Classifier, With A Little Help From DSP

Available in 18 hours and 36 minutes

Live Q&A with John Edwards for the talk titled Building A Tensorflow Lite Neural Network Vibration Classifier, With A Little Help From DSP

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An Introduction To High Efficiency And Multi-rate Digital Filters

Status: Available Now

There are many ways to implement digital filters and many architectures that can be chosen to achieve the optimum performance, which is typically measured in terms of MIPS and memory. This presentation will describe several optimized filtering techniques and architectures and show how they are used.

Examples will include Comb, Polyphase, Cascaded Integrator Comb (CIC) and more.

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Live Q&A with John Edwards - An Introduction To High Efficiency And Multi-rate Digital Filters

Status: Available Now

Live Q&A with John Edwards following his talk titled "An Introduction To High Efficiency And Multi-rate Digital Filters"

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Frequency Domain Signal Processing (2020)

Status: Available Now

Frequency domain signal processing is not just about using the Fast Fourier Transform for calculating a power spectrum, it is also a very efficient method of processing signals compared to traditional time domain techniques. This presentation will describe several common frequency domain algorithms and show how they are used. Examples will include Frequency Domain Filtering, Time Delay Estimation and Interpolation; and more.

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Live Q&A Discussion - Frequency Domain Signal Processing (2020)

Status: Available Now

This is a the live Q&A session for the talk given by John Edwards and titled 'Frequency Domain Signal Processing'

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