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where we have assumed that the prototype filter has been designed according to a frequency-sampling approach so that its Fourier transform G (F) stackrel{{triangle}} sum_{i=0}^{KM-1} g [!i ] e^{-j 2 pi F i} (27).
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Assuming that the prototype coefficients have even symmetry around the coefficient, and the first coefficient is zero [21], we get.
For the sake of simplicity, we will assume that the prototype filter length, denoted, is such that, with being a positive integer.
For simplicity we will assume that the prototype filter length, denoted L, is such that L = bM = 2bN with b a positive integer.
Without loss of generality, let us assume that the prototype filter g(t) can be non zero only when t∈ [ 0,K T] where K represents its overlapping factor.
In particular, let us assume that the prototype filter length can be expressed as L g = α B r − β, (35).
Assuming that the prototype filter is of length MK, the arithmetical computation needed for classical OQAM demodulation yields K′ times M-point FFT (M K log2M CMs), and the polyphase network (PPN) consumes M K2 CMs.
Because Darwin admitted that selection could only set in once the prototype had evolved, it has to be assumed that the origin of the prototype must have been a rare stochastic event.
In the technical literature, it is assumed that the ratio of the maximum prototype to the model concrete aggregate is equal to the scale factor of the specimen.
Assuming that prototypes of intramuscular and surface EMG signals are available, the parameters of the time series model that transforms the intramuscular signals to the surface signals are identified.
Everyone assumed that the case was closed.
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com