Lab No.10: Signal Processing Application

The Morse code is a simple and versatile technique for sending of text messages, mainly using wireless media. The Morse communication was used in 1844 for the first time. The Morse message is based on transmitting of the text using series of on/off tones that can be listened and understood by a skilled operator. Each symbol is represented by a unique sequence of dots and dashes. For sake of coding efficiency, the length of each symbol in the Morse code is related to its frequency of occurrence in English. Morse code is usually transmitted as an amplitude modulated (AM) signal in an on/off keying (OOK) mode. The frequency of the basic audio tone is usually in the range of 600 to 1000Hz in order to ensure a comfortable perception for a human operator. The Morse code can be successfully applied even in a high noise and in a low signal scenarios. We have found no realtime implementation of the Morse decoder on a digital signal processor in references. On the other hand, there are some Morse decoders based on various microcontrollers available. Further, there are available numerous software Morse decoders for PCs, tablets, smartphones etc. They use the sound card input or a line audio input, see e.g. the MRP40 decoder. In contrast to the microcontroller-based Morse decoders which use an analog tone decoder (often the popular phase-locked loop tone decoder NE567) or directly digital pulses of dots and dashes, the presented DSP implementation comprises the added value by involving the digital signal processing for the detection of a Morse signal in a noisy audio signal, or even in the presence of multiple Morse signals.

Patent No.1: US005095197A

Lab No.9: Basic operations using DSPP

In this experiment we studied assembly level programming using TMS320F2835 kit. We performed arithmetic,logical and shift operations. The changes in registers before and after operations were observed. Code composer studio was used.

Lab No.8: Design of FIR filter using sampling method

We designed linear phase FIR filter using frequency sampling method using scilab. The magnitude response was plotted. It was observed if filter order increases ,number of lobes in stop band also increases. We observed that phase is linear and similar to LPF and HPF if order is kept same. If phase is linear output will not be distorted.

Lab No.7: Design of linear phase FIR filter using windowing method

In this experiment we design low pass and high pass linear phase FIR filter. Here we plotted magnitude and phase plot spectrum of both the filters.We observed that phase spectrum was linear. Depending upon the value of passsband attenuation we can choose windowing function: Rectangular,Bartlett,Hamming,Hanning and Blackman.

Lab No.6: Chebyshev Filter Design

A digital Chebyshev filter using the analog filter and input specifications was designed.
Scilab software was used to write the code and also observe the output magnitude spectrum with frequency (Hz) on X axis and attenuation (dB) on Y axis.
The conspicuous feature of the magnitude spectrum was that it exhibited ripple in passband and no monotonic in stop band.
The order of Chebyshev filters was observed to be lesser compared to Butterworth filters for similar input parameters. 
This means that the Chebyshev filter requires less hardware components for its realization.

Lab No.5: Butterworth Filter Design

The task was to design a digital Butterworth filter from an analog filter and with the help of input specifications. Scilab software was used to code and observe the output plot with frequency on x axis and attenuation (in db) on Y axis. 
2 cases were studied: i. the low pass filter, ii. the high pass design.
The pass band attenuation(Ap) and stop band attenuation(As) values which were substituted in the code and the same values were later verified with the help of magnitude spectrum for the corresponding analog pass band and stop band frequencies respectively.
From the pole zero plot observed in Scilab we saw that in case of digital LPF, poles lay inside the unit circle, thus the digital filter was stable in nature.

Lab No.4: Overlap Add/Save Method

The two methods (OAM & OSM) are linear filtering methods. These are block processing techniques and are suitable for real time signal processing.
Both OAM and OSM breakdown the signal into segments , process each segment and then combine the segments into one final output signal. OAM and OSM methods use FFT because high computational speed is achieved using FFT.

Lab No.3: Fast Fourier Transform

FFT method is different than DFT method. In FFT method the input signal is broken into parts according to the Radix-2 algorithm. The input sequence order and the output sequence order in Radix-2 algorithm is in bit reverse manner.
By performing the experiments, we counted the number of steps that were required to perform the FFT. The result was that the steps required for FFT were much less than that of DFT.
Thus, FFT is computationally a fast method.

Lab No.2 : Discrete Fourier Transform

   DFT is a transform method which produces periodic results. Here period is 'N'.

   The spectrum of DFT signal is discrete and is defined in the range from 0 to 2(pi), where 0 is included but 2(pi) is excluded.

   DFT method breaks the continuous signal into parts and takes the values only as particular intervals, therefore this method does not give exact results bt approximate results, hence the spectrum is also approximate.

   The expansion of DFT signal in time domain gives compressed spectrum in frequency domain. And DFT method is computational slow method.

Lab No.1: Convolution and Correlation

Convolution gives the output of the system, whereas Correlation gives the degree of similarity between two signals.

Autocorrelation signal is an Even signal and autocorrelation of delayed signal is same as that of original signal.

Cross correlation of input signal with delayed version of this input signal is same as that of autocorrelation of this original input signal. Correlation is helpful in finding the degree of similarity between two signals.