Is it FFT or similar to it?
QuoteIs it FFT or similar to it?Not even close. If it was that simple there would be no need for PlainFFT, Fix_FFT, FFTW etc.When you subtract the previous measurement from the current one you are computing the slope of the curve which is essentially the derivative (i.e. the rate at which the voltage is changing). So, if you use that to drive the amplitude of a LED it will be brightest where the voltage changes the fastest (usually the loudest part) and dimmest where there's little or no change.Pete
but still i think that the visual is pretty okay
i am in kind of hurry
This is very simplified, but the result of computing the FFT of a signal is an array of numbers . Each element of the array (often referred to as a "bin") corresponds to a small range of frequencies in the input signal. The value in each element allows you to determine the amplitude of the signal corresponding to that frequency.Subtracting successive voltages only tells you the rate at which the voltage is changing. That doesn't tell you what the frequency is. If it did there would be no need for an FFT.Quotei am in kind of hurryYou're really going to have to slow down if you want to understand what the FFT does. To start with, to understand the FFT you have to understand the mathematical concept of complex numbers. If you don't know that, you've got a long way to go.But if you're in a hurry, the executive summary is that what you're doing isn't an FFT.Pete
If I understand it correctly, your algorithm analyses amplitude over time, and assign different amplitudes to your column array. An FFT algorithm, (again, as I understand it), effectively breaks down the incoming signal into different frequency bands (for example, bass frequencies, mid-range frequencies and high-range frequencies) and then analyses the amplitude of each band, which would then be assigned to the columns.