6.6.2 Linear sequences over finite fields.6.6 Initial knowledge on finite fields and linear sequences.6.5 Perfect periodic ACF: minimax binary sequences.6.4 Optimization of aperiodic PSK signals.6.3 Criterion of good aperiodic ACF of APSK signals.6.2 Signals with continuous frequency modulation.6 Spread spectrum signals for time measurement, synchronization and time-resolution.5.6 Processing gain of discrete signals.
#Matlab standard deviation code#
If we change the random seed, nans can occur in different places or even not occur at all. Interestingly, it doesn’t occur for all distributions of random numbers. So, as is shown above, the result is a really small negative number which will turn into a nan when we take the square root of it. 1Ĭ1 = uniform_filter ( x, 3, mode = 'reflect' ) c2 = uniform_filter ( x * x, 3, mode = 'reflect' ) print c1 ] print c2 ] print c2 - c1 * c1 ] std, size = 3 ) ] window_stdev ( x, 3 ) ]Īs is seen above, there are nans present in returned function. around ( x, 2 ) ] generic_filter ( x, np. I haven’t fully tested it, but I am assuming it is a numerical issue. While the fast implementation is fantastic, it does return nans when a part of the array has a standard deviation of zero. A big thank you to nneonneo for the original implementation. A quick implementation of a standard deviation filter in python that produces the same results as the Matlab version. sum ( quick_filt - slow_filt ) - 4.9917e-12Īnd there we are. rand ( 765, 478 ) quick_filt = window_stdev ( x, 5 ) slow_filt = generic_filter ( x, np. Just to prove how much faster this implementation is than the generic filter, here are some benchmarks on different size arrays.įinally, as a sanity check to make sure they both output the same results on randomly sized matrices: 1 \[s_\) which is what was done above since the window size was 3. Matlab defaults to the population standard deviation: I thought maybe python’s implementation was incorrect. I found this out after messing with python’s implementation of a standard deviation filter for half an hour. The default standard deviation in Matlab and python do not return the same value. Recently, I was porting some code from Matlab to python when I came across an interesting bit of information.