Signal Processing Application

This was a Group Experiment performed by Aishwarya Bannore, Varad Choudhari, Gauri Joijode, Amisha Khimani and Apoorva Laharia. We choose "Morse Code Generator from a given Analog Signal" as an application.

Problem Definition : 1) Accept Analogy input and convert it into Digital Signal(Binary).
2) Covert Binary to Morse and implement the dots and dashes as 0 and 1 respectively.
    (Dots = 1 = LED ON, Dash = 0 = LED OFF)

 Patent Review: Morse-to-binary code translator

Patent No.-US 3038030 A
Inventor- Bradley Murray
Publication Date: June 5,1962

Introduction: Currently, conversion of Morse signal into binary signal is done using analog techniques and a shift register. This patent was filed in order to make the existing complex circuit, more simpler.

Review: The proposed system has been implemented using digital techniques and consists of a multi-input binary converter. This system provides a counter for generating pulses indicative of dashes and dots in ratio 2:1. It also provides a converter capable of producing correct digital information with deviations upto 33% from ideal.

IEEE Paper Review : Compression Using Morse Code and Data Patterns

Publishers : A. Nugaliyadde              
                 K.N. Manatunga
                 K.H.D. Perera
Publication Date: February 2014

The paper recommends a bit pattern for the international Morse code that reduces the compression factor. In Morse code, the mostly used letters in words have the least number of signal patterns allowing it to be easy to create and transmit the message. The size of a sentence can be reduced by 34.59% by the proposed method.

Methodology: The Morse Code can be directly used in the data compression. The bits allocated will be 0 for Morse codes‘_’and 1 for‘.’ using a binary converter. Similarly the numbers will take the values according to the Morse code. The space and full stop can be recognized as 1010 and 01010 accordingly. To identify the number of bits allocated for each letter a set of bits is allocated. Since the maximum number of bits allocated for a character is five bits, an octal number format can be used to locate the number of bits given to each character.

By implementing the mentioned techniques,
1. High data compression for texts was approximately 25-30%
2. There is increase in efficiency of transferring data

Future Scope:
1. High level of cryptography can be introduced
2. Bit pattern can be introduced to encrypt text to prevent third party data access
3. An algorithm can be introduced to improve compression

third party accessing the data.

third party accessing the data.

Patent : https://drive.google.com/file/d/0B9FCQ_loE3PaNEZ1bk92NGVyc2s/view?usp=sharing
Reviewed IEEE Paper: https://drive.google.com/file/d/0B9FCQ_loE3Paa3BqeF93WVZwd3c/view?usp=sharing

IEEE Paper - https://drive.google.com/file/d/0B9FCQ_loE3PaY0dlanJTcXlNbUE/view?usp=sharing
Plagiarism Report - https://drive.google.com/file/d/0B9FCQ_loE3PaakNGcXhsMHpaOG8/view?usp=sharing

FIR filter design using frequency sampling method

The aim of the experiment was to design digital filter using frequency sampling method. The magnitude and phase spectrum were plotted for LPF and HPF. 

It was observed that the phase plot is similar. Also, if the order of LPF and HPF are same, then the phase plot for both the filters is also same. The observed and calculated values of As and Ap were verified.

link for the code:

https://drive.google.com/file/d/0B9FCQ_loE3PaQ0haUllPWkMweVk/view?usp=sharing

FIR filter design using windowing method

The aim of the experiment was to design digital filter using windowing method and study the spectrum. The input parameters were passband attenuation(Ap), stopband attenuation(As), passband frequency(Fp), stopband frequency(Fs) and sampling frequency(F). The magnitude and phase spectrum for LPF and BPF using Hanning window were plotted. 

The observed and calculated values of Ap and As were compared. Thus, the values were verified. The phase spectrum was observed to be linear.

Link for the code:

https://drive.google.com/file/d/0B9FCQ_loE3PaNnNxUmdreFBrVzg/view?usp=sharing

Overlap add and Overlap save method

The aim of the experiment was to filter long data sequence using OSM and OAM. The inputs are very large in these methods. They are used for decreasing the output delay. Also, aliasing effect is present in OSM in the initial M-1 samples in the corresponding output block. This effect is absent in OAM.

Link for the codes:
https://drive.google.com/folderview?id=0B9FCQ_loE3PacXlzM1daVVdfb1k&usp=sharing

Operations using DSP Processsor

This was a demonstration experiment comducted by our senior. The operations were performed on a DSP Processor(TMS320F28335). The TI Code Composer Studio(CCS) was used for programming the DSP processor.The various operations carried out were Arithmetic Operations which included Addition Subtraction Multiply Divide, Logical Operations like And and Not and Shifting Operations like Logical Shift Left, Logical Shift Right, Rotate Right, Rotate Left. 

Butterworth filter

This experiment was also performed using Scilab. The input parameters were passband attenuation(Ap), stopband attenuation(As), passband frequency(Fp), stopband frequency(Fs) and sampling frequency(F).The theoretical and observed values of Ap and As were compared.

It was observed that all the poles lie in the unit circle for high pass and low pass digital filter. Thus, the filters are stable. Greater the order of filter, greater is the accuracy in the theoretical and observed values. 

Link for the code:

https://drive.google.com/file/d/0B9FCQ_loE3PaQllUV1hlVjY1Mmc/view?usp=sharing

Chebyshev filter

This was the first experiment performed using Scilab. Digital chebyshev filter was designed using BLT method.

The imput parameters were pass band attenuation(Ap), stop band attenuation(As), pass band frequency(Fp), stop band frequency(Fs) and sampling frequency(F). The observed and theoretical values of Ap and As were compared.

The slight difference in the values were due to variations in constant values and inaccuracies in measurement. More the order of the filter, less will be the difference between observed and theoretical Ap and As values.

Link for the code:

https://drive.google.com/file/d/0B9FCQ_loE3PaQllUV1hlVjY1Mmc/view?usp=sharing

FFT

The aim of the experiment was to perform fast fourier transform of a 4 point sequence. The program was written in C language.

In this experiment, we observed that the number of calculations in FFT are less than that in DFT. Thus, FFT is faster.The number of calculations to implement the DFT equation directly is proportional to N*N, where N is the number of data points. The FFT algorithm reduces this to a number proportional to NlogN where the log is to base 2. 

Link for the codes:

https://drive.google.com/folderview?id=0B9FCQ_loE3PaUVJLamtVRWdkLU0&usp=sharing

DFT

The aim of this experiment was to perform Discrete Fourier Transform.

We observed that as the value of N (length of signal) increases, frequency spacing increases and error decreases.

We plotted the magnitude spectrum when N=4 and also after zero padding i.e when N=8. The magnitude spectrum was found to be symmetric.

Link for programs:

https://drive.google.com/folderview?id=0B9FCQ_loE3PaY1lUZ3NTZUZ0elE&usp=sharing

Convolution and Correlation

The aim of the experiment was to study linear convolution, circular convolution and correlation. In circular convolution, aliasing effect i.e folding of sequence was observed. 

We concluded that in linear convolution, length of output signal N=L+M-1. For circular convolution, length N=max(L,M).

We studied auto-correlation and cross-correlation. For auto-correlation, the observation was that the output signal is a palindrome sequence and the output of correlation is both-sided.

The link for the program is:

https://drive.google.com/drive/folders/0B9FCQ_loE3PaVE14LUZOY1c0T1E