> > if I remember relativity theory correctly, the Big Bang (and, if our > universe is on a contracting trajectory) the Big Crunch are > singularities in both space and time. I guess one can immagine the Bang > and the Crunch warping infinite time at their space-time location. One > can think of it like the bilinear transform that warps infinity to > Fs/2. In that sense, the author's statement is correct. > Talking about smart ass :-). >Hello Andor and others, Fred Hoyle, (The main proponent of the steady state theory of the universe and did not believe in the expanding theory) coyly remarked that the new expanding universe theory must have started with a "big bang". So while he was being a bit of a "wisenheimer", his smart ass description is the one we all now know. He eventually came around and accepted the big bang theory. Clay
2, i'm sure, very simple questions about signal processing
Started by ●January 15, 2005
Reply by ●January 17, 20052005-01-17
Reply by ●January 17, 20052005-01-17
Tim Wescott <tim@wescottnospamdesign.com> wrote:> log fire wrote: > > > > but if you have all tones, lasting for ever, that'd be a continual mass > > of unchanging sound. can these never ending tones change tone? go very > > quiet/silent? change basically? otherwise there wouldn't be any change > > in sound ever. just a massive loud countinual din of all possible > > tones. everything always. > > > Not really -- the Fourier transform shows us that the tones will cancel > each other everywhere but one spot, if they're organized correctly. > > The way one is usually expected to gain insight into this is to do the > math on a bunch of signals. This will cough up some severely > counter-intuitive results indicating that either your math or your > intuition needs adjustment. After you verify your math you're left with > adjusting your intuition.hmm, interesting. what sort of math on signals? what sort of thing would be involved? do you know of any webpages that'd explain / help me get going with the type of thing you're talking about?> > ... > ... > > ... > ... > > > frequencies are interleaved? so the shorter your window the more > > frequencies that are occuring accross the time you're looking at you'll > > miss? > > More or less.great -- thanks for the information.
Reply by ●January 17, 20052005-01-17
log fire wrote:> Tim Wescott <tim@wescottnospamdesign.com> wrote: > > >>log fire wrote: >> >>>but if you have all tones, lasting for ever, that'd be a continual mass >>>of unchanging sound. can these never ending tones change tone? go very >>>quiet/silent? change basically? otherwise there wouldn't be any change >>>in sound ever. just a massive loud countinual din of all possible >>>tones. everything always. >>> >> >>Not really -- the Fourier transform shows us that the tones will cancel >>each other everywhere but one spot, if they're organized correctly. >> >>The way one is usually expected to gain insight into this is to do the >>math on a bunch of signals. This will cough up some severely >>counter-intuitive results indicating that either your math or your >>intuition needs adjustment. After you verify your math you're left with >>adjusting your intuition. > > > hmm, interesting. what sort of math on signals? what sort of thing > would be involved? do you know of any webpages that'd explain / help me > get going with the type of thing you're talking about? > >snip Google on "Fourier Transform". Asking here for a book recommendation may also be a good idea -- there's a large mass of material to be learned, I've always done better with that sort of thing by curling up with a book rather than hitting the net. Rick Lyon's book "Understanding Digital Signal Processing" would be a good book, but you may want to get a signal processing book that'll take you through continuous-time signal processing first. This stuff is generally taught in the second year of a college electronics engineering course -- if you can you may want to see if you can take some classes. -- Tim Wescott Wescott Design Services http://www.wescottdesign.com
Reply by ●January 17, 20052005-01-17
Clay S. Turner wrote:>>if I remember relativity theory correctly, the Big Bang (and, if our >>universe is on a contracting trajectory) the Big Crunch are >>singularities in both space and time. I guess one can immagine the Bang >>and the Crunch warping infinite time at their space-time location. One >>can think of it like the bilinear transform that warps infinity to >>Fs/2. In that sense, the author's statement is correct. >>Talking about smart ass :-). >> > > > Hello Andor and others, > > Fred Hoyle, (The main proponent of the steady state theory of the universe > and did not believe in the expanding theory) coyly remarked that the new > expanding universe theory must have started with a "big bang". So while he > was being a bit of a "wisenheimer", his smart ass description is the one we > all now know. He eventually came around and accepted the big bang theory. > > ClayThere was a stargazer named Hubble Who said, "We expand like a bubble." But fixing the rate Is a source of debate Dissention, contention, and trouble. Jerry -- Engineering is the art of making what you want from things you can get. �����������������������������������������������������������������������
Reply by ●January 17, 20052005-01-17
"Jerry Avins" <jya@ieee.org> wrote in message news:352qsvF4i445sU1@individual.net...> > There was a stargazer named Hubble > Who said, "We expand like a bubble." > But fixing the rate > Is a source of debate > Dissention, contention, and trouble. >There was once a lady named Bright, who traveled much faster than light. She decided one day, to travel quite the relative way, and returned the previous night. author unknown Clay
Reply by ●January 17, 20052005-01-17
Tim Wescott wrote: ...> ASCII doesn't include a "mu", so one uses u.Can you see '�'? it's <ALT>+0181 on a PC numeric pad if your font support it. (Or use 'character map' or 'keycaps'.) ... Jerry -- Engineering is the art of making what you want from things you can get. �����������������������������������������������������������������������
Reply by ●January 17, 20052005-01-17
Jerry Avins wrote:> Tim Wescott wrote: > > ... > > >>ASCII doesn't include a "mu", so one uses u. > > > Can you see '�'? it's <ALT>+0181 on a PC numeric pad if your font > support it. (Or use 'character map' or 'keycaps'.) > > ... > > JerryI can see it, but will it be supported on anyone's reader? -- Tim Wescott Wescott Design Services http://www.wescottdesign.com
Reply by ●January 17, 20052005-01-17
"Jerry Avins" <jya@ieee.org> wrote in message news:352remF4dfqncU1@individual.net...> Tim Wescott wrote: > > ... > > > ASCII doesn't include a "mu", so one uses u. > > Can you see '�'? it's <ALT>+0181 on a PC numeric pad if your font > support it. (Or use 'character map' or 'keycaps'.)The ANSI character set used by Windows does include �--it's character 181 (0xB5). However, since it is one of the upper characters (> 127), it is not nearly as standardized, especially on non-Windows platforms.
Reply by ●January 17, 20052005-01-17
Tim Wescott wrote:> Jerry Avins wrote: > >> Tim Wescott wrote: >> >> ... >> >> >>> ASCII doesn't include a "mu", so one uses u. >> >> >> >> Can you see '�'? it's <ALT>+0181 on a PC numeric pad if your font >> support it. (Or use 'character map' or 'keycaps'.) >> >> ... >> >> Jerry > > > I can see it, but will it be supported on anyone's reader?Most, but not all. It's part of UT-8 and UT-16, which are more than Windows standards. In UT-8 it's B5 (181) and in UT-16 it's 00B5 (0181). Jerry -- Engineering is the art of making what you want from things you can get. �����������������������������������������������������������������������
Reply by ●January 17, 20052005-01-17
In article <10uo4bedfrdt3a3@corp.supernews.com>, Tim Wescott <tim@wescottnospamdesign.com> wrote:> Google on "Fourier Transform". Asking here for a book recommendation > may also be a good idea -- there's a large mass of material to be > learned, I've always done better with that sort of thing by curling up > with a book rather than hitting the net. > > Rick Lyon's book "Understanding Digital Signal Processing" would be a > good book, but you may want to get a signal processing book that'll take > you through continuous-time signal processing first. This stuff is > generally taught in the second year of a college electronics engineering > course -- if you can you may want to see if you can take some classes.ok, thanks for the advise. can i check this with you/anyone please? i'm having a bit of trouble seeing why fourier transforms (whatever they really are), particularly for sound (as opposed to other types of data), should be needed. i'm wondering why can't i ignore, or why would it be a silly idea to ignore, fourier transforms and just start analysing sound data just like i might other types of data such as images or text. (i doubt i'd be considering fourier transforms for those data types). i'm suggesting (just in a questioning kind of way) avoiding ft's and directly accessing audio, sample by sample, and taking my sound analysis (comparing sounds to see how similar they are etc) from there using my own dreampt up methods? with images you can easily directly access each pixel, find out what colour it is, and take it from there with whatever methods you fancy / can think of. dreampt up methods for image analysis have the potential to be perfectly successful i think. what's different, if anything, about sound? (and a further confusion, i realise that dsp isn't just about sound, but images and other signals -- any signals i guess). is it something like this maybe: single samples from a sound signal are like single pixels in an image. that is a perfectly reasonable and good analogy. *but* frequencies are on a higher level than single samples though. like textures in an image are on a higher level than single pixels (numerous pixels are needed and some kind of pattern / relationship goes on to make up a texture -- which needs to be understood/recognised). and with text, words and meanings are on higher levels than individual characters. in order to extract/see these higher level pieces of information, with whatever type of data (sounds, images, text), you need some kind of logic that almost understands the data in order to show the higher level information. nobody's forcing me to use fourier transforms to analyse sound, but if i'm going to analyse sound i'm going to need to have access to frequencies, and fourier transforms are the tested and proven way to get at frequencies. i'd be foolish to attempt to go my own way so far as getting access to frequencies from sound signals. signals to frequencies, so far as sound goes, are fourier transform's forte? and i'd be hard pushed to access the frequencies any other way? is that roughly right? another thing: once having used fourier transforms to get access to frequencies, it'd be ok, and not silly, to then not use fourier transforms? go on and further analyse the frequencies without ft's?
