Saelig Company, Inc. announces the SDS5032E – a new, low-cost two-channel oscilloscope which is packed with useful features normally only seen on higher-end DSOs, including external and video-capable triggering, auto-measurements, auto-scaling, a large 8″ high resolution full color LCD display, XY mode, auto-set, averaging, math functions, USB output, waveform storage, pass/fail output, and a 3-year warranty. FFT functionality is included for frequency spectrum display, in addition to a built-in 6-digit frequency meter, which can measure frequencies from 2Hz to 30MHz.
SDS5032E 30MHz 250MS/s 2-Ch Oscilloscope - [Link]
Andrew built a DIY GPS receiver with an accuracy of ~25m - [via]
A homemade GPS receiver built from the ground up using discrete components and featuring a limiting IF, followed by 1-bit ADC ahead of DSP signal processing in a Xilinx Spartan 3 FPGA. Fast FFT-based search and navigational solutions are computed by “C” code on a Windows PC
Homemade GPS receiver - [Link]
The Fourier transform is a method for representing an irregular signal as a combination of weighted sine waves or ‘frequencies’. To calculate it quickly the Fast Fourier Transform (FFT) was devised some 50 years ago and ever since people have been searching for methods to make it even faster. At MIT a group of researchers has now developed an algorithm that, in a large range of practically important cases, achieves an up to a tenfold speed increase.
Signals whose Fourier transforms contain a relatively small number of strong frequencies are called ‘sparse’. In nature, most of the normal signals are sparse. The new algorithm determines the weights of the strongest frequency components contained in a signal; the sparser the signal, the greater the speedup the algorithm provides. Indeed, if the signal is sparse enough, the algorithm can simply sample it randomly rather than reading it in its entirety. [via]
EFFT – the Even Faster Fourier Transform - [Link]
The purpose of this project is to make an audio visualizer to demonstrate the use of the Nokia 3310 LCD as a graphical display. By audio visualizer, I mean the visualization like Winamp, XMMS, or Windows Media player. This project utilizes a fixed point FFT (fast fourier transform) algorithm to convert the discrete audio samples in time into frequency. This allows us to graph bars for each frequency as the music is playing. In other words, different bars dance around for the bass, midrange, treble, and all the points in between.
Audio Visualization with Nokia 3310 LCD and FFT - [Link]
This project (posted on hobbydebraj) describes a simple spectrum analyzer based on a dsPIC30F4011 microcontroller. It uses Microchip’s FFT library codes to calculate the frequency spectrum of an input signal. The signal conditioning is achieved by a TL084 Op-amp IC. The peaks of spectrum are displayed on a graphics LCD. [via]
A simple spectrum analyzer using dsPIC30F4011 – [Link]
Frontier Nerds have been experimenting with brain wave tech as part of their Mental Block project.
In this well documented project they take the headset from Mattel’s Mind Flex game and hack it to communicate with an Arduino board to measure brain waves and display their levels graphically on a PC via Processing. They chose the Mind Flex device because the board gives access to the FFT of the waves and the relatively low hardware cost.
Brain wave monitor with Arduino + Processing – [Link]
Simon Inns builds this realtime PIC based audio spectrum analyzer. The analyzer uses Fast Fourier Transform routine written in C to run as efficient as possible on the 8 bit PIC18F4550 mcu. The output from the FFT is displayed using a 128×64 graphical LCD to allow a real-time view of an audio signal. [via]
PIC spectrum analyzer uses Fast Fourier Transform routine – [Link]
Here is a basic outline of how this thing works. Everything comes in through the BNC jack on the front. The signal is then attenuated/amplified by the attenuator and amplifier. For the ultimate in excitement and because I dislike switches, the gain of the input stage is controlled by the PIC. The input stage also level shifts the input so it centers around 2.5v (half of full scale) to enable reading negative voltages. The front panel controls ( potentiometers ) are also read by the ADC. Finally, all the exciting info the PIC gathers is displayed on a handy 128×64 Graphics LCD.
The ‘scope can sample an input at up to 750,000 samples per second allowing for signals up to 375kHz to be viewed (sort of). The RMS value of the input is displayed on the main Oscilloscope screen. The FFT function separates the input into 128 frequency bins, and displays the frequency of the bin with the highest amplitude. [via]
Scopey II: Build a dsPIC Oscilloscope and Spectrum Analyzer - [Link]
Cemo has adapted this project for 16×16 dot LED matrix display. You can download the entire project from AVRfreaks (including demonstration movie).
AVR audio spectrum analyser on dot LED matrix display - [Link]
On SG12232C graphical LCD there are two parts displayed: waveform and spectrum. It really looks cool and real when playing music. The program runs on AVR Atmega8 microcontroller clocked at maximum 16MHz frequency. The signal is passed through 8th-order elliptic filter(anti-alias filter) implemented on MAX293. Hardest part in this project was to implement an FFT algorithm which require lots of processing. But Chan has reached 9.6kHz sampling with 75Hz resolution, what is enough for visualisation. Besides firmware author also provides fixed point FFT library optimized for Atmega microcontrollers so anyone could enjoy creating similar projects.
AVR audio spectrum monitor on graphical LCD - [Link]