Lots and lots of home-grown invention: computers, bridges, tunnels, television, radio, transportation, manufacturing, agriculture, the sciences, etc., etc., etc. All the Smithsonian museums have good qualities but American History is my favorite.
Dr. Reed's proposal doesn't really speak to this. He wants smarter receivers that can track a signal and so distinguish wave A from wave B. The technology is not here, not cheap, and certainly not universal.
You are correct on the first point---the article does not really address the state-of-the-art of co-channel signal processing---how to process signals that overlap in frequency, time, and space. I like your explanation of interference.
However, regarding your other points, we do have methods to distinguish wave A from wave B. They are here. We have numerous signal processing techniques for processing co-channel RF/acoustic signals. It might sound like magic, but by imposing one or a few requirements on the transmitted signals---many of which are satisfied in practice---we can:
Separate co-channel signals---simultaneously extract all interfering signals.
Filter one or more co-channel signals without destroying a desired co-channel signal.
Copy (extract) one or more co-channel signals even in the presence of uncopied co-channel interference.
Ignore signals arriving from all but (essentially) one direction.
Ignore signals arriving from (essentially) one direction).
A few examples of the requirements we impose on the transmitted signals to do these sort of things: that they have constant modulus/envelope (e.g., the signal used in GSM phones), that they are statistically independent, that they are digital and use a finite alphabet of transmitted symbols (e.g., one symbol is transmitted for 1 and another for -1).
You are correct on another point: practical systems that incorporate these technologies are NOT cheap, but they do exist, in many different places. For example, some of these ideas are used in GSM transmitters and cell phones.
The article seems to imply that Dr. Reed is a big advocate of these kinds of technology as ONE means of dealing with interference, and they are important.
However, the article incorrectly refers to one of the GNU radio demonstrations as an example of co-channel signal processing. IN FACT, the code he links to takes TWO frequencies as arguments, not one as the author implies. The code just processes two different FM radio stations at the same time, NOT two FM radio stations at the same frequency.
The question "Mathematica vs. Matlab" was recently asked of Slashdot. The conversation was not very far-reaching but there's some good information in there.
However, it's worth pointing out that Matlab has add-on packages for symbolic manipulation (although the end result is not even close to Mathematica's capabilities) and Mathematica has perfectly fine numerical capabilities (although, not nearly as performance-oriented; generally, one is more removed from data in Mathematica than in Matlab).
My guess is: you'll be doing lots and lots and lots of simulations---same code, small tweaks, thousands of iterations. That spells Matlab in my book.
I think I agree with you, for the same reasons: numerical simulation and data processing. Matlab excels in both, although Mathematica can certainly do them.
I also second the suggestion to investigate R. It is vigorously supported by the statistics community, and has numerous add-on packages. A slightly steep learning curve (steeper than Matlab; perhaps no steeper than Mathematica for what you're doing), but very powerful environment.
Ah, yes, excellent suggestion. I can certainly get demo licenses from Matlab. You will be able to try the full version for a limited period of time (say, 30 days). If you're truly focused on getting a computing package, this should be plenty of time to do a proper evaluation. I don't know if Wolfram does a similar thing for Mathematica, but I'd be surprised if they didn't.
A few versions ago, Matlab, indeed, had a crappy language. In fact, I used to keep a long list of all the things I hated about, and all the stupid problems with memory usage, issues in the interpreter, etc., etc. But Matlab 6.x is a significantly different environment. It is essentially a high-level programming language, albeit one targeted at numerical computing. If it was once, it is no longer Fortran's revenge.
As for Mathematica, one could hardly find an environment farther from Fortran.
The formal question you pose is reasonable. However, I must take issue with your first point. You are correct in observing that one should obtain similar answers regardless of the package. However, as in so many other professions, tools matter! I can write in a few lines of Matlab very complicated expressions requiring hundreds of lines of pure C/C++. There are dangers in trying to roll your own libraries (despite it being a useful learning experience); serious numerical analysts don't recommend it. There are support issues (what if you change your algorithm slightly--which environment allows simple modifications?), re-usability issues, etc., etc. This said, I *do* write things in high-level, compiled languages (recent versions of Matlab are actually a member of this group) when I need speed in focused areas. It's always worthwhile to use the right tool for the right job.
Octave is great if you've got the time, will, and skill to support it; if you're in a professional environment, I don't recommend it. For some reason, even though it's been around for years now, a community does not seem to have developed around Octave as has happened for other free/open software. The consequence is that Octave is not nearly as stable, bug-free, and feature-rich as is Matlab. Of course, Matlab costs BIG bucks, so there are trade-offs to be made.
Spacing Imaging has been covered in the press for months, e.g., this article in U.S. News & World Report (the online version doesn't have the same impact as the print article, which had a beautiful, full-page, 1-meter image of Washington D.C.). The company was also featured in the N.Y. Times Sunday January 16th, etc., etc.
Sigurd has done a service for the community, whether he knows it or not. I agree with many others, he's not a naive user, he's a power-user.
But he's collected, in one place, a wealth of knowledge on using Linux day-to-day!
Personal Finance.Moneydance is great!! I am really impressed with it: simple, stable, flexible, smart. This fills a big gap in my day-to-day use of Linux, and gives me another reason to stay out of windows. Anyone using it regularly? Are there comparable personal finance systems out there?
Slashdot Mirror
Shannon's seminal paper created the field of information theory, it's a surprisingly easy read for such an influential paper.
Lots and lots of home-grown invention: computers, bridges, tunnels, television, radio, transportation, manufacturing, agriculture, the sciences, etc., etc., etc. All the Smithsonian museums have good qualities but American History is my favorite.
You are correct on the first point---the article does not really address the state-of-the-art of co-channel signal processing---how to process signals that overlap in frequency, time, and space. I like your explanation of interference.
However, regarding your other points, we do have methods to distinguish wave A from wave B. They are here. We have numerous signal processing techniques for processing co-channel RF/acoustic signals. It might sound like magic, but by imposing one or a few requirements on the transmitted signals---many of which are satisfied in practice---we can:
A few examples of the requirements we impose on the transmitted signals to do these sort of things: that they have constant modulus/envelope (e.g., the signal used in GSM phones), that they are statistically independent, that they are digital and use a finite alphabet of transmitted symbols (e.g., one symbol is transmitted for 1 and another for -1).
You are correct on another point: practical systems that incorporate these technologies are NOT cheap, but they do exist, in many different places. For example, some of these ideas are used in GSM transmitters and cell phones.
The article seems to imply that Dr. Reed is a big advocate of these kinds of technology as ONE means of dealing with interference, and they are important.
However, the article incorrectly refers to one of the GNU radio demonstrations as an example of co-channel signal processing. IN FACT, the code he links to takes TWO frequencies as arguments, not one as the author implies. The code just processes two different FM radio stations at the same time, NOT two FM radio stations at the same frequency.
The question "Mathematica vs. Matlab" was recently asked of Slashdot. The conversation was not very far-reaching but there's some good information in there.
However, it's worth pointing out that Matlab has add-on packages for symbolic manipulation (although the end result is not even close to Mathematica's capabilities) and Mathematica has perfectly fine numerical capabilities (although, not nearly as performance-oriented; generally, one is more removed from data in Mathematica than in Matlab).
My guess is: you'll be doing lots and lots and lots of simulations---same code, small tweaks, thousands of iterations. That spells Matlab in my book.
I also second the suggestion to investigate R. It is vigorously supported by the statistics community, and has numerous add-on packages. A slightly steep learning curve (steeper than Matlab; perhaps no steeper than Mathematica for what you're doing), but very powerful environment.
Ah, yes, excellent suggestion. I can certainly get demo licenses from Matlab. You will be able to try the full version for a limited period of time (say, 30 days). If you're truly focused on getting a computing package, this should be plenty of time to do a proper evaluation. I don't know if Wolfram does a similar thing for Mathematica, but I'd be surprised if they didn't.
As for Mathematica, one could hardly find an environment farther from Fortran.
The formal question you pose is reasonable. However, I must take issue with your first point. You are correct in observing that one should obtain similar answers regardless of the package. However, as in so many other professions, tools matter! I can write in a few lines of Matlab very complicated expressions requiring hundreds of lines of pure C/C++. There are dangers in trying to roll your own libraries (despite it being a useful learning experience); serious numerical analysts don't recommend it. There are support issues (what if you change your algorithm slightly--which environment allows simple modifications?), re-usability issues, etc., etc. This said, I *do* write things in high-level, compiled languages (recent versions of Matlab are actually a member of this group) when I need speed in focused areas. It's always worthwhile to use the right tool for the right job.
Octave is great if you've got the time, will, and skill to support it; if you're in a professional environment, I don't recommend it. For some reason, even though it's been around for years now, a community does not seem to have developed around Octave as has happened for other free/open software. The consequence is that Octave is not nearly as stable, bug-free, and feature-rich as is Matlab. Of course, Matlab costs BIG bucks, so there are trade-offs to be made.
Spacing Imaging has been covered in the press for months, e.g., this article in U.S. News & World Report (the online version doesn't have the same impact as the print article, which had a beautiful, full-page, 1-meter image of Washington D.C.). The company was also featured in the N.Y. Times Sunday January 16th, etc., etc.
But he's collected, in one place, a wealth of knowledge on using Linux day-to-day!
Personal Finance. Moneydance is great!! I am really impressed with it: simple, stable, flexible, smart. This fills a big gap in my day-to-day use of Linux, and gives me another reason to stay out of windows. Anyone using it regularly? Are there comparable personal finance systems out there?