In Ottawa, Ontario, Canada, they have implemented Peaksaver which is a similar thermostat control program during the summer. A great feature is that it also allows the home owner to control their thermostat over the Internet.
These headphones appear to be a simplification on head related transfer functions (HRTF) which has been an active area of research for many years.
For true HRTFs, you really only need a single speaker per ear. You then control interlevel differences (volume differences) between ears as well as interphase differences between ears simulated a sound from a 3D spatial location. The problem is that you also need to have a way of tracking the person's head location and position. If you can track the person's head location then the 3D spatial localization of sound is quite impressive.
It looks like these headphones attempt to approach the problem instead by positioning multiple speakers on each ear. The slight difference in position of the speakers is likely enough to create the delays necessary to change the phase just enough to simulate the 3D spatial localization. It obviously won't be as good since no head tracking is done, but definitely a lot cheaper.
Even though there are separate physical lines that each ADSL user would be using to connect back to the CO, the lines eventually get bundled together. So, while they are still "separated", the fact that they are close together means that there is alot of cross-talk between the different lines. Therefore, for it to work like it does all of the "loud" signals need to be on one end. You can't have the "loud" signals on both ends at the distances ADSL is designed to use. So, reverse ADSL may be possible at the current speeds, but only if EVERYONE used reverse ADSL. You really cannot mix the asymmetry for different lines connected through the same community.
From what I gather from the article, I don't see
how this is very new. Looks like most of this
was done in some degree 20 years ago.
But, past that, I don't believe that fractal
analysis is enough to do that good of a job at
discriminating between different types of music.
You really have to move to multifractals if you
want to do that type of classification properly.
Fractals by themselves don't pay enough attention
to finer details and two pieces of music (I think
someone mention Beethoven's 5th and another
piece) could give very similar fractal results
even though they are very different types of
music. This is because the similar dominant
structures in both pieces of music will give
nearly identical fractal dimensions. Hence,
using multifractals is much better suited.
Actually, I would move towards using relative
multifractals, as introduced in my PhD thesis,
since this will give another level of being
able to compare two pieces of music to check
their similarities.
I wonder why there is the sudden interest in this. While I'll admit that many of my colleagues still haven't figured out that the Gaussian curve is not supreme, it has been known for many decades that most things don't follow straight Gaussian randomness (or white noise as many like to call it). Since I started looking at chaos and fractals many years ago, all of the research I've done and looked at ranging from particular motion, to weather patterns, to fluid dynamics, to DNA, to Internet traffic, to images and textures, to EKG signals, and the list goes on.. have all had very non-Gaussian but still random characteristics. Our descriptions for the randomness was through chaos and fractal theories.
I'm glad to see that this is getting some press time, but, it does seem strange to me since much of this has been known since well before the 1970s as quoted in the articles.
I suppose it is time to get the word out a little more and through off the limiting shackles of the Gaussian distribution and white noise (try brown and pink noise instead.. much more pleasing).
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In Ottawa, Ontario, Canada, they have implemented Peaksaver which is a similar thermostat control program during the summer. A great feature is that it also allows the home owner to control their thermostat over the Internet.
These headphones appear to be a simplification on head related transfer functions (HRTF) which has been an active area of research for many years.
For true HRTFs, you really only need a single speaker per ear. You then control interlevel differences (volume differences) between ears as well as interphase differences between ears simulated a sound from a 3D spatial location. The problem is that you also need to have a way of tracking the person's head location and position. If you can track the person's head location then the 3D spatial localization of sound is quite impressive.
It looks like these headphones attempt to approach the problem instead by positioning multiple speakers on each ear. The slight difference in position of the speakers is likely enough to create the delays necessary to change the phase just enough to simulate the 3D spatial localization. It obviously won't be as good since no head tracking is done, but definitely a lot cheaper.
This is absolutely WRONG!
Even though there are separate physical lines that each ADSL user would be using to connect back to the CO, the lines eventually get bundled together. So, while they are still "separated", the fact that they are close together means that there is alot of cross-talk between the different lines. Therefore, for it to work like it does all of the "loud" signals need to be on one end. You can't have the "loud" signals on both ends at the distances ADSL is designed to use. So, reverse ADSL may be possible at the current speeds, but only if EVERYONE used reverse ADSL. You really cannot mix the asymmetry for different lines connected through the same community.
From what I gather from the article, I don't see
how this is very new. Looks like most of this
was done in some degree 20 years ago.
But, past that, I don't believe that fractal
analysis is enough to do that good of a job at
discriminating between different types of music.
You really have to move to multifractals if you
want to do that type of classification properly.
Fractals by themselves don't pay enough attention
to finer details and two pieces of music (I think
someone mention Beethoven's 5th and another
piece) could give very similar fractal results
even though they are very different types of
music. This is because the similar dominant
structures in both pieces of music will give
nearly identical fractal dimensions. Hence,
using multifractals is much better suited.
Actually, I would move towards using relative
multifractals, as introduced in my PhD thesis,
since this will give another level of being
able to compare two pieces of music to check
their similarities.
I wonder why there is the sudden interest in this. While I'll admit that many of my colleagues still haven't figured out that the Gaussian curve is not supreme, it has been known for many decades that most things don't follow straight Gaussian randomness (or white noise as many like to call it). Since I started looking at chaos and fractals many years ago, all of the research I've done and looked at ranging from particular motion, to weather patterns, to fluid dynamics, to DNA, to Internet traffic, to images and textures, to EKG signals, and the list goes on.. have all had very non-Gaussian but still random characteristics. Our descriptions for the randomness was through chaos and fractal theories.
I'm glad to see that this is getting some press time, but, it does seem strange to me since much of this has been known since well before the 1970s as quoted in the articles.
I suppose it is time to get the word out a little more and through off the limiting shackles of the Gaussian distribution and white noise
(try brown and pink noise instead.. much more pleasing).