![]() ![]() ![]() Note: This is the general version of the overlap save method using inbuilt ifft,fft functions. This segmentation of the input data and the fitting of the output data blocks together form the output sequence. The resulting data sequence from the IDFT are given where the first M-1 points are discarded due to aliasing and the remaining L points constitute the desired result from the linear convolution. To begin the processing, the first M-1 point of the first record is set to zero. To avoid loss of data due to aliasing, the last M-1 points of each data record are saved and these points become the first M-1 data points of the subsequent record. ![]() The last L points of Ym(n) are exactly the same as the result from linear convolution. The latency is reduced to the partition length, at the expense of additional computation compared to traditional overlap-save/overlap-add (though still numerically more efficient than time-domain filtering for long. You can reduce this latency by partitioning the numerator into shorter segments, applying overlap-add or overlap-save over the partitions, and then combining the results to obtain the filtered output. Since the data record is of length N, the first M-1 points of Ym(n)are corrupted by aliasing and must be discarded. Overlap-save and overlap-add introduce a processing latency of N-M+1 samples. The multiplication of the N-point DFTs for the mth block of data yields: Ym(k)=h(k)Xm(k). ![]() The impulse response of the FIR filter is increased in length by appending L-1 zeros and an N-point DFT of the sequence is computed once and stored. Each Data Block consists of the last M-1 data points of the previous block followed by L new data points to form a data sequence of length N=L+M-1.An N point DFT is computed for each data block. In this method, the size of the input data blocks is N=L+M-1 and the DFTs and the IDFTs are of length L. ![]()
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