Normal
Re: FIR filtersI agree. The plotting tool looks cool. One challenge with a time analysis tool like this is how to accurately isolate each frequency in a meaningful way. To isolate the level at a fine frequency resolution takes very narrow band filters. The narrower a filter, the longer the filter impulse response. And when looking at the energy in the output of each "filter", where exactly is time t=0? Looking at his "ideal case" time/frequency colour plot - i.e. the plot of a perfect impulse - the plot itself represents the magnitude of the IR's of the "bands" of filters that he uses. And at low frequencies, the IR's are very long. He solves the "where it time t=0" question by essentially using linear-phase band filters - as seen in the time symmetry of the ideal plot with the energy peaking at the same time across frequency. What he's showing is a similar time/frequency varying behaviour as used in SysTune (TFC window) and it's equivalent in Smaart. His website talks about "bands" of filters but it could be achieved with Fourier transforms (as in Smaart and SysTune). A FFT alone doesn't give the increasingly shorter-in-time effect with increasing frequency that he shows but FFT data can be manipulated to achieve this, or different transform lengths used at different frequencies. (Wavelet transforms inherently have this time/frequency varying behaviour and used to be touted as the answer to every problem in signal processing. I haven't seen them for sometime!) I'm also confused by his descriptions of his amplitude and phase solutions and it seems some information is lost with English not being his first language.
Re: FIR filters
I agree.
The plotting tool looks cool. One challenge with a time analysis tool like this is how to accurately isolate each frequency in a meaningful way. To isolate the level at a fine frequency resolution takes very narrow band filters. The narrower a filter, the longer the filter impulse response. And when looking at the energy in the output of each "filter", where exactly is time t=0? Looking at his "ideal case" time/frequency colour plot - i.e. the plot of a perfect impulse - the plot itself represents the magnitude of the IR's of the "bands" of filters that he uses. And at low frequencies, the IR's are very long. He solves the "where it time t=0" question by essentially using linear-phase band filters - as seen in the time symmetry of the ideal plot with the energy peaking at the same time across frequency.
What he's showing is a similar time/frequency varying behaviour as used in SysTune (TFC window) and it's equivalent in Smaart. His website talks about "bands" of filters but it could be achieved with Fourier transforms (as in Smaart and SysTune). A FFT alone doesn't give the increasingly shorter-in-time effect with increasing frequency that he shows but FFT data can be manipulated to achieve this, or different transform lengths used at different frequencies. (Wavelet transforms inherently have this time/frequency varying behaviour and used to be touted as the answer to every problem in signal processing. I haven't seen them for sometime!)
I'm also confused by his descriptions of his amplitude and phase solutions and it seems some information is lost with English not being his first language.
