digital-filter

I am working on doing some digital filter work using Python and Numpy/Scipy. I'm using scipy.signal.iirdesign to generate my filter coefficents, but it requires the filter passband coefficents in a format I am not familiar with wp, ws : float Passband and stopband edge frequencies, normalized from 0 to 1 (1 corresponds to pi radians / sample). For example: Lowpass: wp = 0.2, ws = 0.3 Highpass: wp = 0.3, ws = 0.2 ( from here ) I'm not familiar with digital filters (I'm coming from a hardware design background). In an analog context, I would determine the desired slope and the 3db down point,

I am programming on an embedded microcontroller (TMS320F28069) a 32-bit floating point MCU. I was going over some of the example projects, and one of them implements a simple FIR filter on ADC sampled data. Block diagram here Let's say the ADC buffer has 10 elements. And let's say the filter has length 3 ( FILTER_LEN=3 ). The filter implementation is pretty straightforward, it starts at the end of the delay chain and moves its way to the beginning. float32 ssfir(float32 *x, float32 *a, Uint16 n) { Uint16 i; // general purpose float32 y; // result float32 *xold; // delay line pointer /*** Setup

I have a range of dates and a measurement on each of those dates. I'd like to calculate an exponential moving average for each of the dates. Does anybody know how to do this? I'm new to python. It doesn't appear that averages are built into the standard python library, which strikes me as a little odd. Maybe I'm not looking in the right place. So, given the following code, how could I calculate the moving weighted average of IQ points for calendar dates? from datetime import date days = [date(2008,1,1), date(2008,1,2), date(2008,1,7)] IQ = [110, 105, 90] (there's probably a better way to

Does anyone know how to use filters in MATLAB? I am not an aficionado, so I'm not concerned with roll-off characteristics etc — I have a 1 dimensional signal vector x sampled at 100 kHz, and I want to perform a high pass filtering on it (say, rejecting anything below 10Hz) to remove the baseline drift. There are Butterworth, Elliptical, and Chebychev filters described in the help, but no simple explanation as to how to implement. There are several filters that can be used, and the actual choice of the filter will depend on what you're trying to achieve. Since you mentioned Butterworth,