## Adventures in Signal Processing with Python

Author’s note: This article was originally called Adventures in Signal Processing with Python (MATLAB? We don’t need no stinkin' MATLAB!) — the allusion to The Treasure of the Sierra Madre has been removed, in deference to being a good neighbor to The MathWorks. While I don’t make it a secret of my dislike of many aspects of MATLAB — which I mention later in this article — I do hope they can improve their software and reduce the price. Please note this...

## How to Estimate Encoder Velocity Without Making Stupid Mistakes: Part I

Here's a common problem: you have a quadrature encoder to measure the angular position of a motor, and you want to know both the position and the velocity. How do you do it? Some people do it poorly -- this article is how not to be one of them.

Well, first we need to get position. Quadrature encoders are incremental encoders, meaning they can only measure relative changes in position. They produce a pair of pulse trains, commonly called A and B, that look like...

## Data Types for Control & DSP

There's a lot of information out there on what data types to use for digital signal processing, but there's also a lot of confusion, so the topic bears repeating.

I recently posted an entry on PID control. In that article I glossed over the data types used by showing "double" in all of my example code. Numerically, this should work for most control problems, but it can be an extravagant use of processor resources. There ought to be a better way to determine what precision you need...

## Debugging DSP code.

I am fascinated with neural network processing and have been playing with them since the 80's.

I am a frequent contributor to the Numenta forum. Numenta is the current project of Jeff Hawins, the guy that gave us the Palm Pilot. They are working with the HTM model. This is a system based on studies of the functions of the cortical column and has some very interesting properties: It processes sequential data streams and has very effective one shot learning. The data is arranged in Sparse...

## Linear Regression with Evenly-Spaced Abscissae

What a boring title. I wish I could come up with something snazzier. One word I learned today is studentization, which is just the normalization of errors in a curve-fitting exercise by the sample standard deviation (e.g. point \( x_i \) is \( 0.3\hat{\sigma} \) from the best-fit linear curve, so \( \frac{x_i - \hat{x}_i}{\hat{\sigma}} = 0.3 \)) — Studentize me! would have been nice, but I couldn’t work it into the topic for today. Oh well.

I needed a little break from...

## Debugging DSP code.

I am fascinated with neural network processing and have been playing with them since the 80's.

I am a frequent contributor to the Numenta forum. Numenta is the current project of Jeff Hawins, the guy that gave us the Palm Pilot. They are working with the HTM model. This is a system based on studies of the functions of the cortical column and has some very interesting properties: It processes sequential data streams and has very effective one shot learning. The data is arranged in Sparse...