DSPP labs

Linear Phase FIR filter design was performed on SciLab for designing both, LPF and HPF. Values of As, Ap, analog passband and stopband frequencies were taken as input from the user. Depending on the value of As chosen, the window function was decided. The window function and the frequency values decided the order of the filter. This way the FIR filter was designed to give h(n) at the output, by using the appropriate window function.

We were given the TMS320F28335 DSP kit with JTAG. We were taught to use the Code Composer Studio v4,0 to write the program on to the DSP processor. The Code Composer Studio allows real time debugging of the program in running mode. The various features of DSP processor can be exploited using this feature. We performed convolution, correlation, DFT, FFT, OAM and OSM on the processor kit. Thus, we got a hands-on experience of the DSP kit.

Subject: Noise reduction Topic: Noise Reduction System The systems using wideband signals like speech use a filterbank and a running cross-correlator to detect narrowband frequencies and analysis-synthesis filterbank to attenuate the wideband signal, in which narrowband frequencies are not detected and to pass or amplify bands narrowband frequency components are detected. In this, narrowband frequencies are not detected. Cross-correlations are obtained from output of two bandpass filters. Low cross-correlation value indicate lesser noise in the signal, while high value of cross-correlation indicate only noise is present. Claims: 1. The system should consist of a first filter with first output and first frequency, and a second filter with second output and second frequency. These have to be 180degrees out of phase around third frequency. These signals are passed through running cross-correlator, which is interconnected to a low-pass filter, and analysis-synthesis filter. 2. Th...

Subject: Noise reduction Topic: Assessing the Effect of Noise-reduction to the Intelligibility of  Low-pass Filtered Speech The residual hearing in hearing-impaired (HI) listeners is due to high frequency elimination in the words or sentences reaching the ear of these listeners. The residual hearing is only due to the low frequency components in the speech. This selective or residual hearing affects the speech intelligibility of the HI listeners. The hearing of these people degrades further in a noisy environment, because the low frequency signals are also affected due to the noise components in the surroundings. One of the solutions found out for enhancing residual hearing is through noise reduction in the signals reaching the ear of the HI people. This helps the low frequency components in high frequency speech can be detected to give highly maximum hearing capability to them. The technique used was that low pass filtered noise- corrupted signals were used at cut-off freq...

Chebyshev filter design was done on Scilab software. Chebyshev HPF and LPF required values of stopband and passband attenuation and frequencies along with the sampling frequency. The attenuation and frquency values were taken same as those of Butterworth filter design. The chebyshev filters have ripple in the passband. Also, the order was found to be lesser than that in the Butterworth filter design. This is a major advantage of chebyshev filter design.

Butterworth filter design was done on Scilab software. We were asked different values of stopband, passband and sampling frequencies for both HPF and LPF. The attenuations in passband and stopband were to be kept in the range; Ap < 3dB and As > 40dB. These values decided the order of the filter and also plotted its magnitude spectrum. The butterworth filter has no ripple in pass band and stop band. Also the order of the filter obtained was high.