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Ye google rulez:D
I can't write exactly because i have no access to that IEEE transactions. But according to abstract it was especially emphasized by authors the non-Gaussian property of exating inputs. So it looks like magnitude-exponential pdf i.e.
p(x) = 0.5*a*exp(-a*|x|)
I think you found your phrase in the "Identification and deconvolution of multichannel linearnon-Gaussian processes using higher order statistics and inverse filtercriteria" article. If it is right the term "onesided" is concerned to time origin of input signals. These signals are causal i.e...
Hi!
First you multiply filter input with blackman window. This is not correct. First you should to calculate windowed sinc function. You shuld multiply original sinc function (with infinite length) with your blackman window. You will obtain low-pass FIR. This FIR you have to store in memory and...
Could you copy-past some text above this phrase?
It is very difficult to understand the meaning "exponential" from one sentance. For example w1(k) and w2(k) may be exponentialy-decayed i.i.d sequences at k>0. Independence in this case is the independence between two sequences but not between...
Hi
What is the algorithm u use for edge detection? It looks like u use simple thresholding. Try to use some gradient-based algorithms like Sobel window. Or some other gradients.
https://en.wikipedia.org/wiki/Sobel_operator
Is the DOA the same as Direction of Arrival? What is the question? Do you want to know how to estimate azimuth and elevation from 2d raster coordinates?
remove dc matlab
You are little wrong. The sentence xx = conv(xx,ones(3,1))/3 is the convolution of input sequence and vector [1/3; 1/3; 1/3]. As I mentioned this sentence looks like sliding average for noice removing.
What kind of features do you want to calculate?
Z-transform: H(z) =...
dc remove matlab
The sentence
xx = conv(xx,ones(3,1))/3;
have no meaning for dc component removing. This term looks like sliding average for removing of high-frequency signal components (or noise). The dc removing itself describing by third term (where mean(xx) - dc bias):
xx =...
First u have to do then u begining your new VLSI design is to search final solution of your problem in Xilinx and Altera sites :))
There are several Verilog examples of FIR on Xilinx site.
Re: how does fourier transform transforms time to freq domai
Fourier Transforn just represent the function of time (your input signal in time domain) as the sum of weighted sines and cosines of certain frequences. This sum of sines and cosines can rewrite throu complex exponents. This is the...
There are some difference between FT in discrete and continious time domains.
1. In continious time domain no convolution between two periodocal signals exists because of the convolution integral grows infinetily.
2. More simly case the convolution between one periodic signal and one...
gyroscope vs accelerometer
As it was mentioned above u need a full-axis strapdown INS for head-movement measurements. Gimbaled INS is not useful for u because it required powerful electromotors and wery complex mecanically.
If u want to measure only static head position u need only three...
Re: correlation problem
Correlation function may have set of local extremums each of them is less than absolytely extremum. You should look for that extremum but not locals.
Re: iir filter design
The frequencys in discrete time lies in interval from 0 to 1 (or from 0 to 2pi depends on frequency normalisation). Therefore first you have to set sampling frequency Fs in continious time units (Hz). Then any "digital" f character frequency (bandpass or bandstop or any...
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