Archive for category technical articles

Low noise, low drift techniques

This presentation has a set of clear, well thought out images describing how chopper techniques can reduce 1/f noise, reduce drift, and even how to cancel the nasty charge injection of FET switches. It shows how modulation can reduce noise in a sensor amplifier system.

link to pdf of Kofi Makinwa\’s presentation, Dynamic Offset Cancellation Techniques

I first learned of Kofi Makinwa’s excellent work through the recent IEEE Solid State Circuits magazine, Winter 2010, Vol. 2, No. 1. He demonstrates a clever accelerometer that uses a small air volume as the ‘proof mass’. The Wheatstone bridge has been around a long time, but it’s clear it can be taught some new tricks. This is the first I’ve heard of a ‘nested chopper’ architecture. Great stuff. Check out Makinwa’s other publications at the IEEE.

I’ve spent some time trying to squeeze good data from MEMS sensors, and I know how difficult it can be. These articles show why adding some switches and circuit complexity can really pay off. And it’s only CMOS and FETs, so we get ‘em for free from Moore’s law, right?

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Fourier Transform of 1/f Noise

Here’s a curious article by Steve Smith, author of The Scientist and Engineer’s Guide to Digital Signal Processing, where he shows that 1/f noise is its own Fourier transform!

link to article \”An Interesting Fourier Transform – 1/f Noise\”

I find it much easier to remember complicated ideas when there’s a clear graph. Smith shows a range of graphs, showing that “there is an inverse relationship; if the time domain decays faster, then the frequency domain decays slower, and vice-versa. This means that there must be a certain decay rate that is unique, where both domains are equal.”

Read the article – the mystery of 1/f noise continues. Perhaps the observation of this mathematical property will point toward learning the physical underpinnings that cause 1/f noise.

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Radiometry explained by NIST

The measurement of light is complicated by a variety of units and concepts that are not used in other fields. For example, the ‘light level’ could be measured in units appropriate to the sensitivity of our eyes (lux), or by the power level (Watts) – but that’s confounded by the wavelength (nano-meters, but sometimes Angstroms) and you need to think in steradians, etendue must be conserved … you get the idea.

We’ve written about some of these issues in earlier posts, but this is one big, complete reference manual – a kind of ‘everything you wanted to know about light, but were afraid to ask’ – and it’s from NIST. They call it a ‘Self-Study Manual’ and it’s a clearly written tutorial on optical radiometry.

And it’s a free download. Enjoy. The test is Tuesday.

link to NIST Self Study Manual on Optical Radiation

The official title is The Self-Study Manual on Optical Radiation Measurements, edited by Fred Nicodemus

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Low noise NMR design

Careful consideration of all the elements of a system’s design can lead you to some very improved performance. Imagine improving a benchtop NMR system by making it 60 times lighter (120kg to 2kg), 40 times smaller, and yet 60 times more sensitive!

This article, from the IEEE Journal of Solid State Circuits (Vol. 44, No. 5, May 2009), shows an excellent example of how this occurs.
link to IEEE abstract of  ‘CMOS RF Biosensor Utilizing Nuclear Magnetic Resonance’ by Sun, Liu, Lee, Weissleder, and Ham

I recommend reading the article – it’s very well written, it describes how NMR works, and it details their systems approach to their improved design. Much can be learned here. The use of a resonant circuit for gain (they call it ‘passive amplification’) is detailed in Figure 8 of the article. (It reminded me of the old ‘regenerative’ type radio receivers, back when a vacuum tube had a power gain of about 12).

Put another way, this article shows that the ‘building block’ approach, when off-the-shelf 50 Ohm compatible RF modules are used, makes it easy to build a system that works – but that it leaves out some great performance improvements that are only possible when you analyze the basic system operation and theory. The design improves when you ask questions like ‘why 50 Ohms’ or ‘where does that noise originate and how can I maximize the signal’ and ‘how can I make this work with a much smaller and lighter magnet’? The article also answers ‘now that I can use a small magnet, can I make a custom CMOS IC that performs the RF detection, and seriously reduce system cost and size’?

Buying as much stuff off the shelf is not bad – it’s a great way to get a proof of principle working FAST, and it demonstrates that an idea or technique can work. Nothing says ’success’ like working hardware – it allows the investors, managers and engineers to breathe easier.

But that extra performance gain from really digging into the details of how things work can pay off – in this case, it changes a benchtop lab instrument into a battery operated portable clinical test platform – this opens new opportunities and situations where this NMR system can be utilized.

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CCD Cameras, eyes, and physics

This tech note was motivated by the question – how does the response of our eyes

differ from the response of a CCD camera sensor.

Using the data of a particular Hammamatsu CCD camera as an example,

we compared how silicon ’sees’ to the photopic eye response

and compared both to a Planck black-body curve of a light at a particular

color temperature.


We don’t know what those lumps are in that CCD response curve – maybe some

strange reflection interference??

If you know – tell us!


spectroscopydetectorb-011408

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Vision response vs. Planck’s Black Body Curve

Color temperature is based upon the idea of a Planck black-body radiator.

Here’s a Tech Note that shows how our eyes respond to the Planck Black-Body radiator.

For a lamp filament at a certain ‘color temperature’ there’s a curve of how our eyes

respond to the lamp. Pete put this into a MathCAD model, and there’s a pdf here

that shows off a few nice graphs.


visualresponseintegral-011308

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Silicon Photodetector Units

Our eyes and silicon light detectors see things differently.

AND the units of photometrics differ from units used by normal MKS systems

here’s an Actinica tech note that tries to sort this out, click link for pdf file

silicondetectorphotometricunits-011408

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