DSPP Experiments

Overlap Add method and Overlap Save Method The real time signals available are large data signals. For processing any signal, the whole sequence should be present at the input at the same time. This is not possible for real time signals. so. overlap add method and overlap save method are used. They are block processing techniques as they divide the input sequence into block of data and then calculate the result. Overlap add method performs linear convolution on the data using FFT and the overlapping values are added to compute the result while overlap save method performs circular convolution on the data using FFT and the overlapping values are neglected. These methods are used to decrease the processing time of long signals. 

Fast Fourier Transform Just like DFT, FFT is also used to find the frequency representation of a discrete time signal. The result of FFT is same as that of DFT. But FFT is computationally fast as it uses Cooley and Tuckey's algorithm to find the result. FFT does parallel processing of the input sequence as it decomposes an N point sequence into two sequences i.e. even and odd signals.  In this experiment, FFT of 4 point and 8 point signals was calculated using DITFFT. Comparison of no. of complex addition and multiplications as well as real addition and multiplications required to calculate FFT and DFT prove that FFT is fast.   

Discrete Fourier Transform In this experiment, we calculated the discrete fourier transform of a N point sequence in time domain to obtain an N point sequence in Frequency domain. Hence, using DFT, discrete time data sets are converted into discrete frequency spectrum. DFT gives an approximate spectrum and is computationally slow.  In the first case, the input signal was x[n] was an N point sequence. The output of DFT gave X[k] which was also an N point sequence.                         In the second case, the sequence was padded with zeros at the end.                      In the third case, the input signal was expanded by adding zeros in   between the signal values as shown. All these cases showed that, as the length of signal increases by zero padding: Frequency spacing decreases, app...

DSPP EXPERIMENTS This blog discusses a few simple experiments to analyse signals. I am going to going to explain a few experiments along with their codes. 1. Experiment 1 : Part A : Linear Convolution and Circular Convolution   Convolution is a formal mathematical operation. It  takes two signals as input and produces a third signal.  In linear systems, convolution is used to describe the relationship between three signals of interest: the input signal, the impulse response, and the output signal. This is what I have done in this experiment.   Linear Convolution My first input signal was x[n] which is an L point sequence. My second input signal was h[n] which is an M point signal. I entered the value of L and the values for input signal x[n]. Then I entered the value of M followed by values for signal h[n]. The function Linear_conv() will calculated the the convolution of these two signals and store the values for output signal ...