Exp 10 : Application of DSPP

This was a group Experiment - finding out relevant papers and patents on DSPP applications . We, as a group of 5 – Vaibhav Kanojia, Ayesha Kesharia, Pooja More,Tushar Kumar and myself had to study on IEEE papers and patents which implemented one dimensional signal processing. Our topic was elimination of noise using Comb Filter.
Paper Review:
Topic :Speech Enhancement Using Harmonic Emphasis and Adaptive Comb Filtering
Authors : Wen Jin, Xin Liu, Michael S. Scordilis and Lu Han
Publisher: IEEE
Summary :
In this paper an enhancement method for single-channel speech degraded by additive noise is proposed. A spectral weighting function is derived by constrained optimization to suppress noise in the frequency domain. Two design parameters are included in the suppression gain, noise-flooring parameter and the gain factor. Further enhancement of the harmonics is achieved by adaptive comb filtering derived using the gain factor with a peak-picking algorithm. The performance of the enhancement method was evaluated by the modified bark spectral distance, composite objective measures and listening tests. 

Patent Review
Patent Number: 5,265,042
Inventors: Wayne E. Smith, Jr., Columbia, Md.
Summary:
This patent describes a nonlinear comb filter device and a method for removing harmonic interference from a corrupted signal. A corrupted signal is basically a signal containing an impulsive signal and harmonic interference. The corrupted signal is delayed through a delay line. Each delay line tap is connected to a corresponding input to a nonlinear device. The delay line and the nonlinear device extract the harmonic interference from the corrupted signal. The extracted harmonic interference is then subtracted from the synchronized corrupted-signal in order to produce the impulsive signal of interest.

Exp 9 : Basic Operations using DSP Processor

Until now all the experiments performed were completely software based. This was our first hardware based experiment.We studied how to program DSP Processors using C language and Assembly language. The kit used was TMS320F28375. Instructions required for carrying out basic Arithmetic, Logical, Shift and Rotate Operations were demonstrated by observing values of registers before and after execution. The Software used was Code Composer Studio by Texas Instruments.

Exp 8 : Digital FIR Filter Design using Frequency Sampling Method

For this experiment we used frequency sampling method in order to design the filter. In this method, H(K) is obtained by replacing w=6.28K/N in Hd(w) & by simply applying IDFT to H(k) we can obtain h(n).
We designed LPF & BPF for specified As,Ap,Fp,Fs & Fsamp values. After doing calculations on values derived from magnitude response we obtained As & Ap values. (calculated).

The code was run on Scilab and graph was plotted. The phase response linearly varies with frequency.

DSPP Exp 7 Linear phase FIR filter using windowing method

 This was our first experiment to design FIR filter. The aim of the experiment was to design Linear Phase FIR filter using window function. FIR filter is designed by truncating infinite samples of hd[n] by using window function. Examples of window function include, Hamming window, Bartlet Window, Hanning window, Blackman window etc.

    Filter parametres like Attenuation in Stop band (As) and Pass band (Ap) as well as Pass band frequency, Stop band frequency and sampling frequency were given as input.The magnitude and phase plot of both the filters was plotted using scilab.

DSPP EXP 6 Design of Chebyshev Filter

Just like the previous experiment even this one was performed using Scilab. The procedure here is pretty much the same as that of Butterworth, by giving the input specification we plot the magnitude plot for High pass and Low pass filter. But in this case unlike the butterworth filter plot, ripples were observed in the passband while the stop band was monotonic.It was also observed that the order of the filter was less in chebyshev as compared to butterworth for the same input parametres. Hence chebyshev filter requires less hardware.

DSPP EXP 5 Design of Butterworth Filter

This was the first experiment wherein we used scilab. In this experiment  we gave pass band attenuation (Ap), stop band attenuation (As), pass band frequency (Fp), stop band frequency (Fs) and sampling frequency as inputs. Order of the filter was calculated. We plotted the magnitude plot for Low pass and high pass filter. We observed the parametres  pass band attenuation (Ap), stop band attenuation (As)using the magnitude plot. There were no ripples seen in the pass band or in stop band.Butterworth filter has all it's digital poles inside the unit circle. Hence the filter is stable.