The hardware based demo experiment, we were very excited as it was demonstrated by a senior who knew the dsp processor quite well.basic Instructions required for Arithmetic, Logical and Shift Operations were demonstrated. The changes in the values of the registers before and after execution of each operation were observed. Code Composer Studio was used to compose the code.
Tuesday, April 26, 2016
Friday, April 22, 2016
DSPP APPLICATION
A group experiment to find on technical paper and one patent in signal processing on a 1D signal . The application that we selected was 'Noise Reduction Using Adaptive Filters'. The group members are Kapil Rawal, Prerana Sarode,Chinmay Upadhyae,vaishnav dandge and Harshit Shukla.
Summary
A new adptive algorithm named affine projection is used rather than traditional methods for noise cancelation like LMS and NLMS ,the output is compared on the basis of signal-to-noise ratio.The result showed that affine projection algorithm gave high signal to noise ratio then LMS and NLMS.
FIR Filter Design Using Frequency Sampling
The coding for this was done in SCILAB.The digital filter is designed using frequency sampling method. For LPF and HPF filter Design we have taken Pass band Attenuation (Ap), Stop band Attenuation (As), Pass band Frequency (Fp) in Hz, Stop band Frequency (Fs) in Hz, Sampling Frequency in Hz as an input. I have plotted Magnitude Spectrum and Phase Spectrum and verified the value of Ap and As in pass band and stop band from the spectrum. From magnitude response it is clear that number of lobes increases with increase in order.To obtain the Magnitude and Phase plots. h[n] values of the signal and the magnitude and phase plot was obtained using SCILAB.
fir-fsm
DESIGN OF CHEBYSHEV FILTER
This experiment was same as the last execpt in mathematical equations , The design was implemented for Analog Chebyshev filter using BLT method.Taking Pass band Attenuation (Ap), Stop band Attenuation (As), Pass band Frequency (Fp) in Hz, Stop band Frequency (Fs) in Hz, Sampling Frequency in Hz as an input. magnitude spectrum was plotted and verified the value of Ap and As in pass band and stop band from the spectrum.
chebyshev
DESIGN OF BUTTERWORTH FILTER
The new thing with this experiment was that we used scilab situations came were problem occured with synatx but final we found out solutions to it. We implemented Butterworth filter using attenuation and frequency in stop and pass band and sampling frequency.By using blt method we got the normalised filter for it and denormalised according to the filter .Thus filter was designed after taking its ZT. From the graph we concluded that there are no ripples found in either stop or pass band and with increase in order the slope becomes sharper.
BUTTERWORTH
BUTTERWORTH
FILTERING OF LONG DATA SEQUENCE
We were able to implement this quiet well as compared to last three experiments. In this Implementaion of Long Input Sequence using Overlap Add Method and overlap save method. length of input signal and input signal values as an input are taken from user.Taking length of impulse response and signal values of impulse response as an input from user. Here long input sequence is broken down into small sequences of equal length, then using zero padding and FFT corresponding X[K] is obtained. Then all these X[K] are added to get final output. Overlap add method is used to process real-time signal which have no defined end. overlap save method is used to evaluate discrete convolution between a very long signal X(n) and a finite impulse response h(n).
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