MATLAB: %How can i create this vector? Please I need your help.

matrix manipulationvector

    Vector = [1 1 1 1 1 0 0 2 2 2 2 2 0 0 3 3 3 3 3 ...];

Best Answer

B = 1:50;
Vector = repelem(B, 7);
D = 0;
for j = 1:size(Vector)
    D = D +1;
    if (mod(D, 7) == 0 || mod(D, 7)==6)
        Vector(j) = 0;
    end
end

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MATLAB: How to append cell arrays with a very specific form

As long as your data meet some assumptions:

each group contains exactly the same number of rows (four in your example), and
each row contains one non-empty data value (in columns 2 - 5).
The groups are contiguous.

>> C = {...
'Rating1'	[]	[]	[]	'8'
'Rating1'	[]	[]	'3'	[]
'Rating1'	'2'	[]	[]	[]
'Rating1'	[]	'4'	[]	[]
'Rating2'	'5'	[]	[]	[]
'Rating2'	[]	'6'	[]	[]
'Rating2'	[]	[]	'3'	[]
'Rating2'	[]	[]	[]	'7'
'Rating3'	'7'	[]	[]	[]
'Rating3'	[]	'7'	[]	[]
'Rating3'	[]	[]	'3'	[]
'Rating3'	[]	[]	[]	'7'
};
>> D = permute(reshape(C(:,2:5),4,[],4),[1,3,2]);
>> D(cellfun('isempty',D)) = [];
>> D = [C(1:4:end,1),reshape(D,4,[]).']
D = 
    'Rating1'    '2'    '4'    '3'    '8'
    'Rating2'    '5'    '6'    '3'    '7'
    'Rating3'    '7'    '7'    '3'    '7'

MATLAB: Signal in and signal out need to be shifted to match one another…

Don't know that it'll help your run time unless you can minimize the lags over which you run it, but the basic way to overlay the two is...

c=xcorr(data(:,1),data(:,2),'coeff');        % xcorr for the two vectors
x3=[ceil(length(c)/2)+1:length(c)]';         % zero-th lag is in middle
[~,ic]=max(c(x3));                           % max/location in positive lags
y=circshift(data(:,2),ic);                   % rotate second by that much
plot([1:length(data)]',[data y])             % show the results on the data
legend('1','2','shift')                      % identify who's who...

ADDENDUM 1: Certainly if the data as given are representative, one way to speed it up would be to eliminate the data where both are zero or even at/below the threshold level that you've set. Whether you need to keep those pre- and post-trigger lengths around to adjust the overall sample length in the end depends on the application, of course.

ALTERNATIVE: Again on the presumption the data are representative; w/o the cross-correlation bottleneck. This does depend upon the rise/fall times being as clean as are here and that one can find a suitable threshold for each pair expeditiously...

It needs must be above the early noise into the fast-rise/fall area and yet must not intersect the lower middle level of the lower=magnitude signal. Also it must be a value that isn't in the dataset to make the subsequent test robust. Since it appears that the data are integer-valued, one can assure that by using a fractional value as the threshold.

th=30.5;                         % see above notes
d=diff(sign(data-th));
% look for crossings and find them; look at result of sample case
id=[find(d(:,1)==2) find(d(:,2)==2);find(d(:,1)==-2) find(d(:,2)==-2)]
id =
 610   437
 715   542
shft=diff(id,[],2)
shft =
-173
-173
shft=floor(mean(diff(id,[],2)));   % the actual shift averages
yd=circshift(data(:,2),abs(shft)); % will need the direction logic here

Quick, but more sensitive to noise by far...salt to suit! :)

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MATLAB: How to append cell arrays with a very specific form

MATLAB: Signal in and signal out need to be shifted to match one another…

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