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Tinkering with new languages is fun and worthwhile to a point, but I honestly feel that my time is now better spent learning new problem domains. Languages matter, but the less tangible skills I've developed working across different domains have been more valuable and fundamental. The things I've learned while studying Machine Learning and DSP over the last year are much more broadly applicable than I would have gues…
Tinkering with new languages is fun and worthwhile to a point, but I honestly feel that my time is now better spent learning new problem domains. Languages matter, but the less tangible skills I've developed working across different domains have been more valuable and fundamental. The things I've learned while studying Machine Learning and DSP over the last year are much more broadly applicable than I would have gues…
What are some broadly applicable things you learned from DSP?
I would strongly favor Forth over Joy, but either way concatenative languages are really worth exploring. It seems fair to compare Forth with C, as both deal with hardware and memory rather intimately. Compare a C implementation of a Fisher-Yates shuffle: void shuffle(int *array, int n) { int i, j, tmp; for (i = n - 1; i > 0; i--) { j = rand_int(i + 1); tmp = array[j]; array[j] = array[i]; array[i] = tmp; } } With th…
Earlier quoted context omitted.
What are some broadly applicable things you learned from DSP?
When you start to think of any stream of numbers as a digital signal, a lot of the techniques become useful. For example, user interfaces provide a fairly high-resolution stream of quantifiable user events, like touch positions. Often you want to smooth these in specific ways. If you understand how a low-pass filter works, this is easy.
I would strongly favor Forth over Joy, but either way concatenative languages are really worth exploring. It seems fair to compare Forth with C, as both deal with hardware and memory rather intimately. Compare a C implementation of a Fisher-Yates shuffle: void shuffle(int *array, int n) { int i, j, tmp; for (i = n - 1; i > 0; i--) { j = rand_int(i + 1); tmp = array[j]; array[j] = array[i]; array[i] = tmp; } } With th…
Could you please explain the Forth sample? For instance, which variable is the array?
Earlier quoted context omitted.
When you start to think of any stream of numbers as a digital signal, a lot of the techniques become useful. For example, user interfaces provide a fairly high-resolution stream of quantifiable user events, like touch positions. Often you want to smooth these in specific ways. If you understand how a low-pass filter works, this is easy.
Does one need a background in electronics to understand DSP?
PerlisLanguage(Prolog).
I would strongly favor Forth over Joy, but either way concatenative languages are really worth exploring. It seems fair to compare Forth with C, as both deal with hardware and memory rather intimately. Compare a C implementation of a Fisher-Yates shuffle: void shuffle(int *array, int n) { int i, j, tmp; for (i = n - 1; i > 0; i--) { j = rand_int(i + 1); tmp = array[j]; array[j] = array[i]; array[i] = tmp; } } With th…
Could you please explain the Forth sample? For instance, which variable is the array?
: shuffle
( addr len -- addr )
1- for
for(int z=n; z >= 0; z--) {}
( addr )
i 1+ random
( addr rand_int(i+1) )
over +
( addr (rand_int(i+1)+addr) )
over i +
( addr (rand_int(i+1)+addr) (i+addr) )
swap@
next ;
Earlier quoted context omitted.
Does one need a background in electronics to understand DSP?
Not at all. In fact I'd say most DSP these days is done entirely in software.