I would like to wite a note about simple first order RC circuits.
Thursday, April 21, 2016
Sunday, April 17, 2016
Adaptive Filter: BMFLC
In this article, I will discuss about adaptive noise canceling techniques such as
FLC estimates the quasiperiodic signal of known frequency by using least mean square (LMS) algorithm to adapt the amplitude and phase of a reference signal. WFLC is an extension of FLC which can adapt to a periodic signal of unknown frequency and amplitude. Consequently, WFLC also adapts to time-varying reference signal frequencies while FLC can only estimate a signal with fixed and known frequency. To eliminate the time lag which is not desirable in real-time application, a method using combination of WFLC-FLC has been proposed. One limitation of WFLC is its inability to extract a periodic or quasi-periodic signal containing more than one dominant frequency. To overcome that, BMFLC approach tracks a predetermined band of multiple dominant frequencies based on the prior knowledge of the desired signal. The adaption process is achieved using LMS optimization similar to WFLC and FLC. As the frequency components in BMFLC are constant, analytical ouble integration can be employed to obtain the displacement from acceleration. Due to this reason, it becomes an ideal choice for applications where data is sensed with accelerometers.
- Fourier Linear Combiner (FLC)
- Weighted-frequency Fourier Linear Combiner (WFLC)
- Bandlimited Multiple Fourier Linear Combiner (BMFLC)
FLC estimates the quasiperiodic signal of known frequency by using least mean square (LMS) algorithm to adapt the amplitude and phase of a reference signal. WFLC is an extension of FLC which can adapt to a periodic signal of unknown frequency and amplitude. Consequently, WFLC also adapts to time-varying reference signal frequencies while FLC can only estimate a signal with fixed and known frequency. To eliminate the time lag which is not desirable in real-time application, a method using combination of WFLC-FLC has been proposed. One limitation of WFLC is its inability to extract a periodic or quasi-periodic signal containing more than one dominant frequency. To overcome that, BMFLC approach tracks a predetermined band of multiple dominant frequencies based on the prior knowledge of the desired signal. The adaption process is achieved using LMS optimization similar to WFLC and FLC. As the frequency components in BMFLC are constant, analytical ouble integration can be employed to obtain the displacement from acceleration. Due to this reason, it becomes an ideal choice for applications where data is sensed with accelerometers.
Setup
Arduino zero pro is used for the experiment. The code are written in C so that it can be ported to other platforms easily. Firstly, a reference signal is generated which is superimposed with noise. The generated signal is filtered with adaptive filter. The filtered output is compared with the reference signal by plotting them on serial plotter. The latest version Arduino IDE has not only Serial Monitor but it also has Serial Plotter. Therefore, it is easy and convenient to plot and see them serial plotter how an adaptive filter adapts to its input signal.Tuesday, April 12, 2016
Using 3rd party CC2530 modules
I would like to talk about 3rd party CC2530 modules - ( a first one and a second one ) that I bought from Aliexpress. In a previous article, I talked about CC2530DK from TI. In this post, using SmartRF05EB to debug 3rd party module is discussed.
Figure. A small CC2530 module whose size is 13 mm x 18 mm.
Figure. A small CC2530 module whose size is 13 mm x 18 mm.
Subscribe to:
Posts (Atom)