How to signal divide into windows of lengths [1024] .

Question

Rasheed Majeed 2021-11-16

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回答： Star Strider 2021-11-16

I have a signal x which is 43939 , which I want to divide into windows of lengths [1024] where each window overlaps with 50% of the previous window.using 1024 as an example I want the whole signal to be divided to windows of length 1024 where each window overlaps with the previous by 50% like 1:1024 then 512:1536 and store each window how can I implement that using a for loop or if statement then how to I use discrete wavelet transform (DWT) for the signal decomposion to 10 levels

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Answer 1

Dave B 2021-11-16

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How about assembling up a matrix marking the indices of x you want. Of course you'll have to do something so that it's divisible by 512 (like pad the end).

x=rand(1,43939);
% pad at the end?
x=padarray(x,[0 512-mod(numel(x),512)],nan,'post');
start=(1:512:numel(x)-512)';
ind=start+(0:1023);
% just a view of what this looks like:
ind(1:3,1:5)
ans = 3×5
           1           2           3           4           5
         513         514         515         516         517
        1025        1026        1027        1028        1029
ind(1:3,end-5:end)
ans = 3×6
        1019        1020        1021        1022        1023        1024
        1531        1532        1533        1534        1535        1536
        2043        2044        2045        2046        2047        2048
y = x(ind);

For the wavelet bit, it sounds like wavedec, but that's about all I know.

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Rasheed Majeed 2021-11-16

Thank you very much

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Answer 2

Star Strider 2021-11-16

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Use the buffer function. It will do everything desired.

signal = 1:100;
winlen = 10;                                            % WindowLength
overlap = fix(winlen/2);                                % 50% Overlap
out = buffer(signal, winlen, overlap)
out = 10×20
     0     1     6    11    16    21    26    31    36    41    46    51    56    61    66    71    76    81    86    91
     0     2     7    12    17    22    27    32    37    42    47    52    57    62    67    72    77    82    87    92
     0     3     8    13    18    23    28    33    38    43    48    53    58    63    68    73    78    83    88    93
     0     4     9    14    19    24    29    34    39    44    49    54    59    64    69    74    79    84    89    94
     0     5    10    15    20    25    30    35    40    45    50    55    60    65    70    75    80    85    90    95
     1     6    11    16    21    26    31    36    41    46    51    56    61    66    71    76    81    86    91    96
     2     7    12    17    22    27    32    37    42    47    52    57    62    67    72    77    82    87    92    97
     3     8    13    18    23    28    33    38    43    48    53    58    63    68    73    78    83    88    93    98
     4     9    14    19    24    29    34    39    44    49    54    59    64    69    74    79    84    89    94    99
     5    10    15    20    25    30    35    40    45    50    55    60    65    70    75    80    85    90    95   100

The wavelet decomposition then depends in part on the sort of wavelet that will give the best results for the intended decomposition. I have not used wavelets frequently enought to consider myself skilled in their use, so I do not feel comfortable commenting on that part.

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