I have a little code, that should implement cepstrum deconvolution for minimum phase FIR filter design, but being nonmatlab guy I'm struggling with understanding it. Can someone help?
wn = [ones(1,m)
2*ones((n+odd)/2-1,m)
ones(1-rem(n,2),m)
zeros((n+od d)/2-1,m)];
y = real(ifft(exp(fft(wn.*real(ifft(log(abs(fft(x)))))))));
Mainly I don't understand the first line, ".*" symbol in second line and also probably at some point there should be conversion from real to complex domain in the second line, but I have no idea where. Any ideas?
In the first line you are constructing the matrix wn row by row.
.* operator means element-wise multiplication. * alone would mean matrix multiplication.
In fact you should pay attention to the size of x and wn which must be the same for the element-wise multiplication to have sense.
actually there isn't any conversion from real to complex in the second line. There are the functions log, fft, ifft that may return complex values depending on the input.
You can access the Matlab help by the commands help or doc (for example doc ones should produce the documentation of the ones function - this produce a matrix filled with ones of the size specified by it's arguments).
To quickly summon the help when you're inspecting some code you can use Matlab's inline help by pressing the button F1 when the cursor is at the end of a function name (just before the parenthesis).
Related
I need to compute this equation with MATLAB:
where Sn can be both matrices or scalar and I tried to do it with
S_A = S_3*S_5*((ones-(S_1*S_5)).^(-1))*S_2+S_4
The problem is it doesn't give me the right result and the problem it seems to be with the difference but I cannot figure why is giving me wrong results.
The result is supposed to be this one
but the MATLAB result is
I don't understand why the two results are not the same.
The only way that I figured is through this
diff = ones-(S_1*S_5);
if S_1*S_5 == zeros %Perchè senza non funziona?
diff = ones;
else
diff = (ones-(S_1*S_5)).^(-1)
end
S_A = S_3*S_5*diff*S_2+S_4;
But I don't think it's a smart solution. Anyone knows why I'm not getting the correct results?
"I tried to do it with S_A = S_3*S_5*((ones-(S_1*S_5)).^(-1))*S_2+S_4"
The problem here is that A^(-1) in mathematical notation means "take the inverse", whereas you used A. ^(-1), note the dot, which in MATLAB's notation means "take the each matrix element to the power -1". Taking the inverse of a matrix is not smart in MATLAB anyway, be it via inv() or ^(-1), instead, use mldivide:
S_A = S_3*S_5*(eye(size(S_1*S_5,1))-(S_1*S_5))\S_2+S_4
Also, as mentioned in Brice's answer use eye, not ones to create an identity matrix, and feed it a size argument as opposed to nothing. All in all it looks to me like you do not have a firm grasp of basic MATLAB functionality, so I'd like to point you to The MathWorks own tutorial on MATLAB.
ones outputs a matrix filled with ones, not the identitiy matrix which is given by function eye.
You also need to specify the size of ones or eye, otherwise it will simply output a scalar 1 (i.e. a 1-by-1 matrix filled with ones, or the 1-by-1 identity matrix).
Try (assuming all matrices have the same size):
siz=length(S_1);
S_A = S_3*S_5*((eye(siz)-(S_1*S_5))^(-1))*S_2+S_4
Here is the given system I want to plot and obtain the vector field and the angles they make with the x axis. I want to find the index of a closed curve.
I know how to do this theoretically by choosing convenient points and see how the vector looks like at that point. Also I can always use
to compute the angles. However I am having trouble trying to code it. Please don't mark me down if the question is unclear. I am asking it the way I understand it. I am new to matlab. Can someone point me in the right direction please?
This is a pretty hard challenge for someone new to matlab, I would recommend taking on some smaller challenges first to get you used to matlab's conventions.
That said, Matlab is all about numerical solutions so, unless you want to go down the symbolic maths route (and in that case I would probably opt for Mathematica instead), your first task is to decide on the limits and granularity of your simulated space, then define them so you can apply your system of equations to it.
There are lots of ways of doing this - some more efficient - but for ease of understanding I propose this:
Define the axes individually first
xpts = -10:0.1:10;
ypts = -10:0.1:10;
tpts = 0:0.01:10;
The a:b:c syntax gives you the lower limit (a), the upper limit (c) and the spacing (b), so you'll get 201 points for the x. You could use the linspace notation if that suits you better, look it up by typing doc linspace into the matlab console.
Now you can create a grid of your coordinate points. You actually end up with three 3d matrices, one holding the x-coords of your space and the others holding the y and t. They look redundant, but it's worth it because you can use matrix operations on them.
[XX, YY, TT] = meshgrid(xpts, ypts, tpts);
From here on you can perform whatever operations you like on those matrices. So to compute x^2.y you could do
x2y = XX.^2 .* YY;
remembering that you'll get a 3d matrix out of it and all the slices in the third dimension (corresponding to t) will be the same.
Some notes
Matlab has a good builtin help system. You can type 'help functionname' to get a quick reminder in the console or 'doc functionname' to open the help browser for details and examples. They really are very good, they'll help enormously.
I used XX and YY because that's just my preference, but I avoid single-letter variable names as a general rule. You don't have to.
Matrix multiplication is the default so if you try to do XX*YY you won't get the answer you expect! To do element-wise multiplication use the .* operator instead. This will do a11 = b11*c11, a12 = b12*c12, ...
To raise each element of the matrix to a given power use .^rather than ^ for similar reasons. Likewise division.
You have to make sure your matrices are the correct size for your operations. To do elementwise operations on matrices they have to be the same size. To do matrix operations they have to follow the matrix rules on sizing, as will the output. You will find the size() function handy for debugging.
Plotting vector fields can be done with quiver. To plot the components separately you have more options: surf, contour and others. Look up the help docs and they will link to similar types. The plot family are mainly about lines so they aren't much help for fields without creative use of the markers, colours and alpha.
To plot the curve, or any other contour, you don't have to test the values of a matrix - it won't work well anyway because of the granularity - you can use the contour plot with specific contour values.
Solving systems of dynamic equations is completely possible, but you will be doing a numeric simulation and your results will again be subject to the granularity of your grid. If you have closed form solutions, like your phi expression, they may be easier to work with conceptually but harder to get working in matlab.
This kind of problem is tractable in matlab but it involves some non-basic uses which are pretty hard to follow until you've got your head round Matlab's syntax. I would advise to start with a 2d grid instead
[XX, YY] = meshgrid(xpts, ypts);
and compute some functions of that like x^2.y or x^2 - y^2. Get used to plotting them using quiver or plotting the coordinates separately in intensity maps or surfaces.
I have a rather large piece of code at the end of which I need to apply ifft to an array ZF. ZF is the fft of the columns of a matrix Z.
The problem is, the ifft turns out to be a complex double array (which it shouldn't if I did everything correctly) so I need a debugging tool to check at which point of the numerous manipulations I performed on the original DFT I lost the Hermitian Symmetry.
The array is a double 1024x1376
my attempt at this is:
for i=2:N/2
Herm=ZF(i,:)+ZF(N-i+2,:);
end
N=1024 is the number of rows and if Herm is purely real then I have the Symmetry.
Any thoughts? I'm still on the first month of MATLAB so if I'm way off feel free to tell me.
I have a problem.
I have a task to write an own fft2 without using for-loops in Matlab.
There is a formula for computing this task:
F(u,v) = sum (0 to M-1) {sum(o to N-1) {f(m,n)*e^(-i*2pi*(um/M + vn/N))}}
Or for better reading:
http://www.directupload.net/file/d/3808/qs3r9ogz_png.htm
It is easy to do it with two for-loops but I have no idea how to do this without these loops, absolutely no idea.
We get no help by the teaching personal. They don't even give a hint or a reference to a book, where we could read about it.
Now, I want to try to get help here.
Are you familiar with the matrix form of DFT? have a look here: http://en.wikipedia.org/wiki/DFT_matrix
You can do something similar in order to get a matrix form for 2D DFT.
You need to transformation matrices. The first is a N-by-N DFT matrix that operates on the columns of f, as explained in the link above. Next you need another M-byM DFT matrix the operates on the rows of f. Finally, you transformed signal is given by
F = Wm * f * Wn;
without any loops.
Note that the DFT matrix can be constructed also without loop by using something like
(1:M)*((1:M)')
Just a little correction in Thp's answer: (1:M)*((1:M)') is not the right way to create the matrix, but (1:M)'*(1:M) is the correct way.
I have a dataset Sig of size 65536 x 192 in Matlab. If I want to take the one-dimensional fft along the second dimension, I could either do a for loop:
%pre-allocate ect..
for i=1:65536
F(i,:) = fft(Sig(i,:));
end
or I could specify the dimension and do it without the for loop:
F = fft(Sig,[],2);
which is about 20 times faster for my dataset.
I have looked for something similar for the discrete wavelet transform (dwt), but been unable to find it. So I was wondering if anyone knows a way to do dwt across a specified dimension in Matlab? Or do I have to use for loops?
In your loop FFT example, it seems you operate on lines. Matlab use a Column-major order. It may explain the difference of performance. Is the performance the same if you operate on columns ?
If this is the right explanation, you could use dwt in a loop.
A solution if you really need performance is to do your own MEX calling a C discrete wavelet transform library the way you want.
I presume you're using the function from the Wavelet Toolbox: http://www.mathworks.co.uk/help/toolbox/wavelet/ref/dwt.html
The documentation doesn't seem to describe acting on an array, so it's probably not supported. If it does allow you to input an array, then it will operate on the first non-singleton dimension or it will ignore the shape and treat it as a vector.